https://nmsl.cs.sfu.ca/api.php?action=feedcontributions&feedformat=atom&user=NkhodabaNMSL - User contributions [en-ca]2026-06-04T06:35:23ZUser contributionsMediaWiki 1.35.1https://nmsl.cs.sfu.ca/index.php?title=File:Pariya.jpg&diff=4998File:Pariya.jpg2012-06-16T01:42:51Z<p>Nkhodaba: </p>
<hr />
<div></div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4911Private:progress-khodabakhshi2012-05-23T22:18:28Z<p>Nkhodaba: </p>
<hr />
<div>= Summer 2012 (RA) =<br />
<br />
===May===<br />
* Working on my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/thesis/ thesis].<br />
* Addressing TOMCCAP paper comments.<br />
* Reviewing two MM12 short papers.<br />
* Running new experiments to cover change of frame rate, as asked by TOMCCAP reviewer.<br />
* Implementing GUI for two [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/code/java/trunk/CSpider/ Cspider] applications.<br />
<br />
= Spring 2012 (RA) =<br />
* Courses: <br />
**CMPT828 Illumination in Images and Video<br />
**CMPT894 Cloud Computing Directed Reading<br />
<br />
===April===<br />
* Course project of CMPT828.<br />
* Implementing video registration and copy detection application.<br />
* Preparing the spider demo [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/mm12-3dvcd/doc/mm12.pdf doc].<br />
* Working on Cloud Computing [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/CloudComputing/doc/CloudComputing.pdf report].<br />
<br />
===March 30===<br />
* Working on VCD companies and TRECVID [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/VCDCompanies-Survey/VCDCompanies-TRECVID.pdf survey].<br />
<br />
* Reviewing the assigned TOMCCAP journal.<br />
<br />
* Working on CSpider [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/Report-CSpiderDesign/doc/reportTemplate.pdf design].<br />
<br />
* Implementing some parts of createSignatureLib of CSpider.<br />
<br />
===Feb 29===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Working on my talk for the 828 course.<br />
<br />
* Preparing for MMSys presentation.<br />
<br />
* Attended the MMSys conference.<br />
<br />
* Working on VCD companies survey.<br />
<br />
===Jan 27===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Exploring a new visual signature which details is explained in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/Report_1-1-12 report]<br />
<br />
* Reading "Introduction to Cloud Computing" book by Timothy Chou.<br />
* Reading "Cloud Application Architectures: Building Applications and Infrastructure in the Cloud" book by George Reese.<br />
<br />
= Fall 2011 =<br />
* Internship<br />
<br />
= Summer 2011 (RA) =<br />
* Courses: <br />
**CMPT826 (dropped)<br />
<br />
===June 14===<br />
* New results added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4905Private:progress-khodabakhshi2012-05-16T01:59:23Z<p>Nkhodaba: </p>
<hr />
<div>= Summer 2012 (RA) =<br />
<br />
===May===<br />
* Working on my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/thesis/ thesis].<br />
* Addressing TOMCCAP paper comments.<br />
* Reviewing two MM12 short papers.<br />
* Running new experiments to cover change of frame rate, as asked by TOMCCAP reviewer.<br />
<br />
= Spring 2012 (RA) =<br />
* Courses: <br />
**CMPT828 Illumination in Images and Video<br />
**CMPT894 Cloud Computing Directed Reading<br />
<br />
===April===<br />
* Course project of CMPT828.<br />
* Implementing video registration and copy detection application.<br />
* Preparing the spider demo [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/mm12-3dvcd/doc/mm12.pdf doc].<br />
* Working on Cloud Computing [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/CloudComputing/doc/CloudComputing.pdf report].<br />
<br />
===March 30===<br />
* Working on VCD companies and TRECVID [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/VCDCompanies-Survey/VCDCompanies-TRECVID.pdf survey].<br />
<br />
* Reviewing the assigned TOMCCAP journal.<br />
<br />
* Working on CSpider [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/Report-CSpiderDesign/doc/reportTemplate.pdf design].<br />
<br />
* Implementing some parts of createSignatureLib of CSpider.<br />
<br />
===Feb 29===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Working on my talk for the 828 course.<br />
<br />
* Preparing for MMSys presentation.<br />
<br />
* Attended the MMSys conference.<br />
<br />
* Working on VCD companies survey.<br />
<br />
===Jan 27===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Exploring a new visual signature which details is explained in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/Report_1-1-12 report]<br />
<br />
* Reading "Introduction to Cloud Computing" book by Timothy Chou.<br />
* Reading "Cloud Application Architectures: Building Applications and Infrastructure in the Cloud" book by George Reese.<br />
<br />
= Fall 2011 =<br />
* Internship<br />
<br />
= Summer 2011 (RA) =<br />
* Courses: <br />
**CMPT826 (dropped)<br />
<br />
===June 14===<br />
* New results added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4904Private:progress-khodabakhshi2012-05-16T01:58:52Z<p>Nkhodaba: </p>
<hr />
<div>= Summer 2012 (RA) =<br />
<br />
===May===<br />
* Working on my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/thesis/ thesis].<br />
* Addressing TOMCCAP paper comments.<br />
* Reviewing two MM12 short papers.<br />
* Running new experiments to cover change of frame, as asked by TOMCCAP reviewer.<br />
<br />
= Spring 2012 (RA) =<br />
* Courses: <br />
**CMPT828 Illumination in Images and Video<br />
**CMPT894 Cloud Computing Directed Reading<br />
<br />
===April===<br />
* Course project of CMPT828.<br />
* Implementing video registration and copy detection application.<br />
* Preparing the spider demo [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/mm12-3dvcd/doc/mm12.pdf doc].<br />
* Working on Cloud Computing [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/CloudComputing/doc/CloudComputing.pdf report].<br />
<br />
===March 30===<br />
* Working on VCD companies and TRECVID [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/VCDCompanies-Survey/VCDCompanies-TRECVID.pdf survey].<br />
<br />
* Reviewing the assigned TOMCCAP journal.<br />
<br />
* Working on CSpider [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/Report-CSpiderDesign/doc/reportTemplate.pdf design].<br />
<br />
* Implementing some parts of createSignatureLib of CSpider.<br />
<br />
===Feb 29===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Working on my talk for the 828 course.<br />
<br />
* Preparing for MMSys presentation.<br />
<br />
* Attended the MMSys conference.<br />
<br />
* Working on VCD companies survey.<br />
<br />
===Jan 27===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Exploring a new visual signature which details is explained in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/Report_1-1-12 report]<br />
<br />
* Reading "Introduction to Cloud Computing" book by Timothy Chou.<br />
* Reading "Cloud Application Architectures: Building Applications and Infrastructure in the Cloud" book by George Reese.<br />
<br />
= Fall 2011 =<br />
* Internship<br />
<br />
= Summer 2011 (RA) =<br />
* Courses: <br />
**CMPT826 (dropped)<br />
<br />
===June 14===<br />
* New results added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4887Private:progress-khodabakhshi2012-05-09T20:48:16Z<p>Nkhodaba: </p>
<hr />
<div>= Summer 2012 (RA) =<br />
<br />
===May===<br />
* Working on my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/thesis/ thesis].<br />
* Addressing TOMCCAP paper comments.<br />
* Reviewing two MM12 short papers.<br />
<br />
= Spring 2012 (RA) =<br />
* Courses: <br />
**CMPT828 Illumination in Images and Video<br />
**CMPT894 Cloud Computing Directed Reading<br />
<br />
===April===<br />
* Course project of CMPT828.<br />
* Implementing video registration and copy detection application.<br />
* Preparing the spider demo [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/mm12-3dvcd/doc/mm12.pdf doc].<br />
* Working on Cloud Computing [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/CloudComputing/doc/CloudComputing.pdf report].<br />
<br />
===March 30===<br />
* Working on VCD companies and TRECVID [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/VCDCompanies-Survey/VCDCompanies-TRECVID.pdf survey].<br />
<br />
* Reviewing the assigned TOMCCAP journal.<br />
<br />
* Working on CSpider [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/Report-CSpiderDesign/doc/reportTemplate.pdf design].<br />
<br />
* Implementing some parts of createSignatureLib of CSpider.<br />
<br />
===Feb 29===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Working on my talk for the 828 course.<br />
<br />
* Preparing for MMSys presentation.<br />
<br />
* Attended the MMSys conference.<br />
<br />
* Working on VCD companies survey.<br />
<br />
===Jan 27===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Exploring a new visual signature which details is explained in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/Report_1-1-12 report]<br />
<br />
* Reading "Introduction to Cloud Computing" book by Timothy Chou.<br />
* Reading "Cloud Application Architectures: Building Applications and Infrastructure in the Cloud" book by George Reese.<br />
<br />
= Fall 2011 =<br />
* Internship<br />
<br />
= Summer 2011 (RA) =<br />
* Courses: <br />
**CMPT826 (dropped)<br />
<br />
===June 14===<br />
* New results added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4886Private:progress-khodabakhshi2012-05-09T20:46:07Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2012 (RA) =<br />
* Courses: <br />
**CMPT828 Illumination in Images and Video<br />
**CMPT894 Cloud Computing Directed Reading<br />
<br />
===May===<br />
* Working on my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/thesis/ thesis].<br />
* Addressing TOMCCAP paper comments.<br />
* Reviewing two MM12 short papers.<br />
<br />
===April===<br />
* Course project of CMPT828.<br />
* Implementing video registration and copy detection application.<br />
* Preparing the spider demo [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/mm12-3dvcd/doc/mm12.pdf doc].<br />
* Working on Cloud Computing [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/CloudComputing/doc/CloudComputing.pdf report].<br />
<br />
===March 30===<br />
* Working on VCD companies and TRECVID [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/VCDCompanies-Survey/VCDCompanies-TRECVID.pdf survey].<br />
<br />
* Reviewing the assigned TOMCCAP journal.<br />
<br />
* Working on CSpider [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/Report-CSpiderDesign/doc/reportTemplate.pdf design].<br />
<br />
* Implementing some parts of createSignatureLib of CSpider.<br />
<br />
===Feb 29===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Working on my talk for the 828 course.<br />
<br />
* Preparing for MMSys presentation.<br />
<br />
* Attended the MMSys conference.<br />
<br />
* Working on VCD companies survey.<br />
<br />
===Jan 27===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Exploring a new visual signature which details is explained in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/Report_1-1-12 report]<br />
<br />
* Reading "Introduction to Cloud Computing" book by Timothy Chou.<br />
* Reading "Cloud Application Architectures: Building Applications and Infrastructure in the Cloud" book by George Reese.<br />
<br />
= Fall 2011 =<br />
* Internship<br />
<br />
= Summer 2011 (RA) =<br />
* Courses: <br />
**CMPT826 (dropped)<br />
<br />
===June 14===<br />
* New results added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4878Private:progress-khodabakhshi2012-05-01T19:03:14Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2012 (RA) =<br />
* Courses: <br />
**CMPT828 Illumination in Images and Video<br />
**CMPT894 Cloud Computing Directed Reading<br />
<br />
===April===<br />
* Course project of CMPT828.<br />
* Implementing video registration and copy detection application.<br />
* Preparing the spider demo [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/mm12-3dvcd/doc/mm12.pdf doc].<br />
* Working on Cloud Computing [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/CloudComputing/doc/CloudComputing.pdf report].<br />
<br />
===March 30===<br />
* Working on VCD companies and TRECVID [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/VCDCompanies-Survey/VCDCompanies-TRECVID.pdf survey].<br />
<br />
* Reviewing the assigned TOMCCAP journal.<br />
<br />
* Working on CSpider [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/Report-CSpiderDesign/doc/reportTemplate.pdf design].<br />
<br />
* Implementing some parts of createSignatureLib of CSpider.<br />
<br />
===Feb 29===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Working on my talk for the 828 course.<br />
<br />
* Preparing for MMSys presentation.<br />
<br />
* Attended the MMSys conference.<br />
<br />
* Working on VCD companies survey.<br />
<br />
===Jan 27===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Exploring a new visual signature which details is explained in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/Report_1-1-12 report]<br />
<br />
* Reading "Introduction to Cloud Computing" book by Timothy Chou.<br />
* Reading "Cloud Application Architectures: Building Applications and Infrastructure in the Cloud" book by George Reese.<br />
<br />
= Fall 2011 =<br />
* Internship<br />
<br />
= Summer 2011 (RA) =<br />
* Courses: <br />
**CMPT826 (dropped)<br />
<br />
===June 14===<br />
* New results added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4848Private:progress-khodabakhshi2012-04-23T07:18:36Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2012 (RA) =<br />
* Courses: <br />
**CMPT828 Illumination in Images and Video<br />
**CMPT894 Cloud Computing Directed Reading<br />
<br />
===April===<br />
* Course project of CMPT828.<br />
* Implementing video registration and copy detection application.<br />
* Working on Cloud Computing [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/CloudComputing/doc/CloudComputing.pdf report].<br />
<br />
===March 30===<br />
* Working on VCD companies and TRECVID [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/VCDCompanies-Survey/VCDCompanies-TRECVID.pdf survey].<br />
<br />
* Reviewing the assigned TOMCCAP journal.<br />
<br />
* Working on CSpider [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/Report-CSpiderDesign/doc/reportTemplate.pdf design].<br />
<br />
* Implementing some parts of createSignatureLib of CSpider.<br />
<br />
===Feb 29===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Working on my talk for the 828 course.<br />
<br />
* Preparing for MMSys presentation.<br />
<br />
* Attended the MMSys conference.<br />
<br />
* Working on VCD companies survey.<br />
<br />
===Jan 27===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Exploring a new visual signature which details is explained in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/Report_1-1-12 report]<br />
<br />
* Reading "Introduction to Cloud Computing" book by Timothy Chou.<br />
* Reading "Cloud Application Architectures: Building Applications and Infrastructure in the Cloud" book by George Reese.<br />
<br />
= Fall 2011 =<br />
* Internship<br />
<br />
= Summer 2011 (RA) =<br />
* Courses: <br />
**CMPT826 (dropped)<br />
<br />
===June 14===<br />
* New results added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4841Private:progress-khodabakhshi2012-04-05T21:17:34Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2012 (RA) =<br />
* Courses: <br />
**CMPT828 Illumination in Images and Video<br />
**CMPT894 Cloud Computing Directed Reading<br />
<br />
===April===<br />
* Course project of CMPT828.<br />
* Implementing video registration and copy detection application.<br />
<br />
===March 30===<br />
* Working on VCD companies and TRECVID [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/VCDCompanies-Survey/VCDCompanies-TRECVID.pdf survey].<br />
<br />
* Reviewing the assigned TOMCCAP journal.<br />
<br />
* Working on CSpider [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/Report-CSpiderDesign/doc/reportTemplate.pdf design].<br />
<br />
* Implementing some parts of createSignatureLib of CSpider.<br />
<br />
===Feb 29===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Working on my talk for the 828 course.<br />
<br />
* Preparing for MMSys presentation.<br />
<br />
* Attended the MMSys conference.<br />
<br />
* Working on VCD companies survey.<br />
<br />
===Jan 27===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Exploring a new visual signature which details is explained in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/Report_1-1-12 report]<br />
<br />
* Reading "Introduction to Cloud Computing" book by Timothy Chou.<br />
* Reading "Cloud Application Architectures: Building Applications and Infrastructure in the Cloud" book by George Reese.<br />
<br />
= Fall 2011 =<br />
* Internship<br />
<br />
= Summer 2011 (RA) =<br />
* Courses: <br />
**CMPT826 (dropped)<br />
<br />
===June 14===<br />
* New results added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4840Private:progress-khodabakhshi2012-04-03T18:47:27Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2012 (RA) =<br />
* Courses: <br />
**CMPT828 Illumination in Images and Video<br />
**CMPT894 Cloud Computing Directed Reading<br />
<br />
===March 30===<br />
* Working on VCD companies and TRECVID [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/VCDCompanies-Survey/VCDCompanies-TRECVID.pdf survey].<br />
<br />
* Reviewing the assigned TOMCCAP journal.<br />
<br />
* Working on CSpider [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/Report-CSpiderDesign/doc/reportTemplate.pdf design].<br />
<br />
* Implementing some parts of createSignatureLib of CSpider.<br />
<br />
===Feb 29===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Working on my talk for the 828 course.<br />
<br />
* Preparing for MMSys presentation.<br />
<br />
* Attended the MMSys conference.<br />
<br />
* Working on VCD companies survey.<br />
<br />
===Jan 27===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Exploring a new visual signature which details is explained in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/Report_1-1-12 report]<br />
<br />
* Reading "Introduction to Cloud Computing" book by Timothy Chou.<br />
* Reading "Cloud Application Architectures: Building Applications and Infrastructure in the Cloud" book by George Reese.<br />
<br />
= Fall 2011 =<br />
* Internship<br />
<br />
= Summer 2011 (RA) =<br />
* Courses: <br />
**CMPT826 (dropped)<br />
<br />
===June 14===<br />
* New results added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4825Private:progress-khodabakhshi2012-03-13T07:17:20Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2012 (RA) =<br />
* Courses: <br />
**CMPT828 Illumination in Images and Video<br />
**CMPT894 Cloud Computing Directed Reading<br />
<br />
===March 30===<br />
* Working on VCD companies and TRECVID [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/VCDCompanies-Survey/VCDCompanies-TRECVID.pdf survey].<br />
<br />
* Reviewing the assigned TOMCCAP journal.<br />
<br />
* Working on CSpider [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/Report-CSpiderDesign/doc/reportTemplate.pdf design].<br />
<br />
===Feb 29===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Working on my talk for the 828 course.<br />
<br />
* Preparing for MMSys presentation.<br />
<br />
* Attended the MMSys conference.<br />
<br />
* Working on VCD companies survey.<br />
<br />
===Jan 27===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Exploring a new visual signature which details is explained in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/Report_1-1-12 report]<br />
<br />
* Reading "Introduction to Cloud Computing" book by Timothy Chou.<br />
* Reading "Cloud Application Architectures: Building Applications and Infrastructure in the Cloud" book by George Reese.<br />
<br />
= Fall 2011 =<br />
* Internship<br />
<br />
= Summer 2011 (RA) =<br />
* Courses: <br />
**CMPT826 (dropped)<br />
<br />
===June 14===<br />
* New results added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4818Private:progress-khodabakhshi2012-03-05T19:36:09Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2012 (RA) =<br />
* Courses: <br />
**CMPT828 Illumination in Images and Video<br />
**CMPT894 Cloud Computing Directed Reading<br />
<br />
===March 30===<br />
* Working on VCD [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/VCDCompanies-Survey/VCDCompanies-TRECVID.pdf survey].<br />
<br />
===Feb 29===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Working on my talk for the 828 course.<br />
<br />
* Preparing for MMSys presentation.<br />
<br />
* Attended the MMSys conference.<br />
<br />
* Working on VCD companies survey.<br />
<br />
===Jan 27===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Exploring a new visual signature which details is explained in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/Report_1-1-12 report]<br />
<br />
* Reading "Introduction to Cloud Computing" book by Timothy Chou.<br />
* Reading "Cloud Application Architectures: Building Applications and Infrastructure in the Cloud" book by George Reese.<br />
<br />
= Fall 2011 =<br />
* Internship<br />
<br />
= Summer 2011 (RA) =<br />
* Courses: <br />
**CMPT826 (dropped)<br />
<br />
===June 14===<br />
* New results added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4815Private:progress-khodabakhshi2012-03-01T18:53:28Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2012 (RA) =<br />
* Courses: <br />
**CMPT828 Illumination in Images and Video<br />
**CMPT894 Cloud Computing Directed Reading<br />
<br />
===Feb===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Working on my talk for the 828 course.<br />
<br />
* Preparing for MMSys presentation.<br />
<br />
* Attended the MMSys conference.<br />
<br />
* Working on VCD companies survey.<br />
<br />
===Jan 27===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Exploring a new visual signature which details is explained in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/Report_1-1-12 report]<br />
<br />
* Reading "Introduction to Cloud Computing" book by Timothy Chou.<br />
* Reading "Cloud Application Architectures: Building Applications and Infrastructure in the Cloud" book by George Reese.<br />
<br />
= Fall 2011 =<br />
* Internship<br />
<br />
= Summer 2011 (RA) =<br />
* Courses: <br />
**CMPT826 (dropped)<br />
<br />
===June 14===<br />
* New results added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4796Private:progress-khodabakhshi2012-02-25T22:50:22Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2012 (RA) =<br />
* Courses: <br />
**CMPT828 Illumination in Images and Video<br />
**CMPT894 Cloud Computing Directed Reading<br />
<br />
===Feb===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Working on my talk for the 828 course.<br />
<br />
* Preparing for MMSys presentation.<br />
<br />
* Attended the MMSys conference.<br />
<br />
===Jan 27===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Exploring a new visual signature which details is explained in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/Report_1-1-12 report]<br />
<br />
* Reading "Introduction to Cloud Computing" book by Timothy Chou.<br />
* Reading "Cloud Application Architectures: Building Applications and Infrastructure in the Cloud" book by George Reese.<br />
<br />
= Fall 2011 =<br />
* Internship<br />
<br />
= Summer 2011 (RA) =<br />
* Courses: <br />
**CMPT826 (dropped)<br />
<br />
===June 14===<br />
* New results added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4785Private:progress-khodabakhshi2012-02-14T18:28:40Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2012 (RA) =<br />
* Courses: <br />
**CMPT828 Illumination in Images and Video<br />
**CMPT894 Cloud Computing Directed Reading<br />
<br />
===Feb===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Working on my talk for the 828 course.<br />
<br />
* Preparing for MMSys presentation.<br />
<br />
===Jan 27===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Exploring a new visual signature which details is explained in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/Report_1-1-12 report]<br />
<br />
* Reading "Introduction to Cloud Computing" book by Timothy Chou.<br />
* Reading "Cloud Application Architectures: Building Applications and Infrastructure in the Cloud" book by George Reese.<br />
<br />
= Fall 2011 =<br />
* Internship<br />
<br />
= Summer 2011 (RA) =<br />
* Courses: <br />
**CMPT826 (dropped)<br />
<br />
===June 14===<br />
* New results added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=People&diff=4782People2012-01-30T04:56:59Z<p>Nkhodaba: </p>
<hr />
<div>==Faculty ==<br />
<br />
* [http://www.cs.sfu.ca/~mhefeeda/ Mohamed Hefeeda]<br />
<br />
* [http://www.cs.sfu.ca/~peters/ Joseph G. Peters]<br />
<br />
<br/><br />
<center><br />
{| border="0"<br />
|[[Image:Mhefeeda.jpg|center|Mohamed Hefeeda|100px]]<br />
|[[Image:Peters.jpg|center|Joseph Peters|100px]]<br />
|-<br />
|align="center" width="200pt"|Mohamed Hefeeda<br />
|align="center" width="200pt"|Joseph G. Peters<br />
|}<br />
</center><br />
<br />
== Current Students ==<br />
<br />
{| border="0"<br />
|width="500pt"|<br />
* [http://www.sfu.ca/~aah10/ Ahmed Hamza, Ph.D.]<br />
|[ [[Private:progress-hamza|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* Saleh Almowuena, Ph.D.<br />
|[ [[Private:progress-almowuena|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* [http://www.cs.sfu.ca/~ssa121/personal/ Somsubhra Sharangi (PhD)]<br />
|[ [[Private:progress-sharangi|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* [http://www.sfu.ca/~tdameh/ Taher Dameh, M.Sc.]<br />
|[ [[Private:progress-dameh|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* Azin Dastpak, M.Sc. (co-supervised with Prof. Jiangchuan Liu)<br />
|[ [[Private:progress-dastpak|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* Kaushik Choudhary, M.Sc.<br />
|[ [[Private:progress-choudhary|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* [http://www.sfu.ca/~nkhodaba/ Naghmeh Khodabakhshi, M.Sc.]<br />
|[ [[Private:progress-khodabakhshi|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* Ahmed Bu-khamsin, M.Sc.<br />
|[ [[Private:progress-bu-khamsin|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* Abdullah Aldhamin, M.Sc.<br />
|[ [[Private:progress-aldhamin|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* [http://www.sfu.ca/~masumr/ Md. Mahfuzur Rahman (Masum), M.Sc.]<br />
|[ [[Private:progress-rahman|Progress]] ]<br />
|}<br />
<br />
<br />
<br />
<br/><br />
<center><br />
{| border="0"<br />
|[[Image:Ahamza.JPG|center|Ahmed Hamza|80x100px]]<br />
|[[Image:saleh_small.jpg|center|Saleh Almowuena|80x100px]]<br />
|[[Image:Som.JPG|center|Somsubhra Sharangi|80x100px]]<br />
|-<br />
|align="center" align="center" width="100pt"|Ahmed Hamza<br />
|align="center" align="center" width="100pt"|Saleh Almowuena<br />
|align="center" align="center" width="100pt"|Somsubhra Sharangi<br />
|}<br />
{| border="0"<br />
|[[Image:Taher.jpg|center|Taher Dameh|80x100px]]<br />
|[[Image:Azin.jpg|center|Azin Dastpak|80x100px]]<br />
|[[Image:Kaushik.jpg|center|Kaushik Choudhary|80x100px]]<br />
|[[Image:Naghmeh.jpg|center|Naghmeh Khodabakhshi|80x100px]]<br />
|-<br />
|align="center" align="center" width="100pt"|Taher Dameh<br />
|align="center" align="center" width="100pt"|Azin Dastpak<br />
|align="center" align="center" width="100pt"|Kaushik Choudhary<br />
|align="center" align="center" width="100pt"|Naghmeh Khodabakhshi<br />
|}<br />
{| border="0"<br />
|[[Image:AhmedBuKhamsin.jpg|center|Ahmed Bu-khamsin|80x100px]]<br />
|[[Image:Abdullah_small.jpg|center|Abdullah Aldhamin|80x100px]]<br />
|[[Image:Masum.jpg|center|Md. Mahfuzur Rahman|80x100px]]<br />
|-<br />
|align="center" align="center" width="100pt"|Ahmed Bu-khamsin<br />
|align="center" align="center" width="100pt"|Abdullah Aldhamin<br />
|align="center" align="center" width="100pt"|Md. Mahfuzur Rahman<br />
|}<br />
</center><br />
<br />
<br />
== Visitors ==<br />
<br />
* Gordon Leung, Undergraduate (NSERC USRA, Summer 2010)<br />
<br />
* Andreas Berger, Graduate (Research Visitor from The Telecommunications Research Center Vienna, Feb -- May 2009)<br />
<br />
* Vikas Kumar, Undergraduate (Research Internship, May -- July 2008) <br />
<br />
* Nitin Chiluka, Undergraduate (Research Internship, December 2007 -- May 2008)<br />
<br />
* Nicolas Gomez, Undergraduate (NSERC USRA, Summer 2007)<br />
<br />
* Pouya Alagheband, Undergraduate (NSERC USRA, Summer 2007)<br />
<br />
<br />
== Graduated Students ==<br />
<br />
<br />
'''Ph.D. Students'''<br />
<br />
* ChengHsin Hsu, Ph.D., Fall 2009, [http://nsl.cs.surrey.sfu.ca/theses/hsu09.pdf Efficient Mobile Multimedia Streaming]. First Job: Senior Researcher, Deutsche Telekom R&D Lab, California, USA. Since 2011, he has been an Assistant Professor, Department of Computer Science, National Tsing Hua University, Taiwan. <br />
<br />
<br />
'''M.Sc. Students -- Thesis Option (thesis = 15 credits)'''<br />
<br />
* Fei Gao, M.Sc., Fall 2011, [http://nsl.cs.surrey.sfu.ca/theses/gao11.pdf Distributed Approximate Spectral Clustering for Large-Scale Datasets]<br />
<br />
* R. Cameron Harvey, M.Sc., Fall 2011, Spatio-Temporal Video Copy Detection<br />
<br />
* Hamed Sadeghi Neshat, M.Sc., Summer 2011, Effective Online Advertising<br />
<br />
* Farid Molazem Tabrizi, M.Sc., Spring 2011, [http://nsl.cs.surrey.sfu.ca/theses/tabrizi11.pdf Adaptive Transmission of Variable-Bit-Rate Video Streams to Mobile Devices] (co-supervised with Prof. Joseph Peters) <br />
<br />
* Shabnam Mirshokraie, M.Sc., Fall 2010, [http://nsl.cs.surrey.sfu.ca/theses/mirshokraie10.pdf Live Peer-to-Peer Streaming with Scalable Video Coding and Network Coding]<br />
<br />
* Somsubhra Sharangi, M.Sc., Fall 2010, [http://nsl.cs.surrey.sfu.ca/theses/sharangi10.pdf Scalable Video Streaming over WiMAX Networks] (co-supervised with Prof. Ramesh Krishnamurti)<br />
<br />
* Yuanbin Shen, M.Sc., Summer 2010, [http://nsl.cs.surrey.sfu.ca/theses/shen10.pdf Efficient Algorithms for Multi-sender Data Transmission in Swarm-based Peer-to-peer Streaming Systems]<br />
<br />
* Cong Ly, M.Sc., Summer 2010, [http://nsl.cs.surrey.sfu.ca/theses/ly10.pdf Latency Reduction in Online Multiplayer Games Using Detour Routing]<br />
<br />
* Yi Liu, M.Sc., Fall 2009, [http://nsl.cs.surrey.sfu.ca/theses/liu09.pdf Video Streaming over Cooperative Wireless Networks]<br />
<br />
* Greg Kowalski, M.Sc., Fall 2009, [http://nsl.cs.surrey.sfu.ca/theses/kowalski09.pdf Empirical Analysis of Multi-Sender Segment Transmission Algorithms in Peer-to-Peer Streaming]<br />
<br />
* Kianoosh Mokhtarian, M.Sc., Fall 2009, [http://nsl.cs.surrey.sfu.ca/theses/mokhtarian09.pdf Efficient and Secure Delivery of Scalable Video Streams]<br />
<br />
* Behrooz Noorizadeh, M.Sc., Fall 2007, [http://nsl.cs.surrey.sfu.ca/theses/noorizadeh07.pdf Cooperative Proxy Caching for Peer-to-Peer Traffic]<br />
<br />
* Hossein Ahmadi, M.Sc., Summer 2007, [http://nsl.cs.surrey.sfu.ca/theses/ahmadi07.pdf Probabilistic Coverage and Connectivity in Wireless Sensor Networks]<br />
<br />
* Majid Bagheri, M.Sc., Summer 2007, [http://nsl.cs.surrey.sfu.ca/theses/bagheri07.pdf Efficient K-Coverage Algorithms for Wireless Sensor Networks and their Applications to Early Detection of Forest Fires]<br />
<br />
* Osama Saleh, M.Sc., Fall 2006 [http://nsl.cs.surrey.sfu.ca/theses/saleh06.pdf Modeling and Caching of Peer-to-Peer Traffic]<br />
<br />
<br />
'''M.Sc. Students -- Project Option (project = 6 credits)'''<br />
<br />
* Mohammad Alkurbi, M.Sc., Spring 2011, [http://nsl.cs.surrey.sfu.ca/theses/alkurbi11.pdf Detection of Botnets Mounted on the Session Initiation Protocol]<br />
<br />
<br />
<br />
<br/><br />
<center><br />
{| border="0"<br />
|[[Image:Fei.jpg|center|Fei Gao|80x100px]]<br />
|[[Image:Cameron.jpg|center|R. Cameron Harvey|80x100px]]<br />
|-<br />
|align="center" align="center" width="100pt"|Fei Gao<br />
|align="center" align="center" width="100pt"|R. Cameron Harvey<br />
|}<br />
{| border="0"<br />
|[[Image:Hamed.jpg|center|Hamed SadeghiNeshat|80x100px]]<br />
|[[Image:Mohammad.jpg|center|Mohammad Alkurbi|80x100px]]<br />
|[[Image:Farid.jpg|center|Farid Molazem Tabrizi|80x100px]]<br />
|[[Image:Shabnam.jpg|center|Shabnam Mirshokraie|80x100px]]<br />
|[[Image:Som.JPG|center|Somsubhra Sharangi|80x100px]]<br />
|-<br />
|align="center" align="center" width="100pt"|Hamed SadeghiNeshat<br />
|align="center" align="center" width="100pt"|Mohammad Alkurbi<br />
|align="center" align="center" width="100pt"|Farid Molazem Tabrizi<br />
|align="center" align="center" width="100pt"|Shabnam<br/>Mirshokraie<br />
|align="center" align="center" width="100pt"|Somsubhra Sharangi<br />
|}<br />
{| border="0"<br />
|[[Image:Yuanbin.jpg|center|Yuanbin Shen|80x100px]]<br />
|[[Image:Cong.jpg|center|Cong Ly|80x100px]]<br />
|[[Image:Cheng.JPG|center|ChengHsin Hsu|80x100px]]<br />
|[[Image:Liuyi.jpg|center|Yi Liu|80x100px]]<br />
|[[Image:Greg.jpg|center|Greg Kowalski|80x100px]]<br />
|-<br />
|align="center" align="center" width="100pt"|Yuanbin Shen<br />
|align="center" width="100pt"|Cong Ly<br />
|align="center" width="100pt"|ChengHsin Hsu<br />
|align="center" width="100pt"|Yi Liu<br />
|align="center" width="100pt"|Greg Kowalski<br />
|}<br />
{| border="0"<br />
|[[Image:Kianoosh.jpg|center|Kianoosh Mokhtarian|80x100px]]<br />
|[[Image:Behrooz.jpg|center|Behrooz Noorizadeh|80x100px]]<br />
|[[Image:Ahmadi.jpg|center|Hossein Ahmadi|80x100px]]<br />
|[[Image:Mbagheri.jpg|center|Majid Bagheri|80x100px]]<br />
|[[Image:Saleh.jpg|center|Osama Saleh|80x100px]]<br />
|-<br />
|align="center" width="100pt"|Kianoosh Mokhtarian<br />
|align="center" width="100pt"|Behrooz<br/>Noorizadeh<br />
|align="center" width="100pt"|Hossein Ahmadi<br />
|align="center" width="100pt"|Majid Bagheri<br />
|align="center" width="100pt"|Osama Saleh<br />
|}<br />
<br />
</center><br />
<br />
== Contacts == <br />
<br />
* [[Private:contacts|List of contact persons in academia and industry (Login Required). ]]</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4775Private:progress-khodabakhshi2012-01-28T01:33:27Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2012 (RA) =<br />
* Courses: <br />
**CMPT828 Illumination in Images and Video<br />
**CMPT894 Cloud Computing Directed Reading<br />
<br />
===Jan 27===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Exploring a new visual signature which details is explained in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/Report_1-1-12 report]<br />
<br />
* Reading "Introduction to Cloud Computing" book by Timothy Chou.<br />
* Reading "Cloud Application Architectures: Building Applications and Infrastructure in the Cloud" book by George Reese.<br />
<br />
= Fall 2011 =<br />
* Internship<br />
<br />
= Summer 2011 (RA) =<br />
* Courses: <br />
**CMPT826 (dropped)<br />
<br />
===June 14===<br />
* New results added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4765Private:progress-khodabakhshi2012-01-27T00:50:54Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2012 (RA) =<br />
* Courses: <br />
**CMPT828 Illumination in Images and Video<br />
**CMPT894 Cloud Computing Directed Reading<br />
<br />
===Jan 27===<br />
* Working on the TOMCCAP [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-projects/3DVideo/3DVCopyDetection/documents/tomccap12/ draft]<br />
<br />
* Exploring a new visual signature which details is explained in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/Report_1-1-12 report]<br />
<br />
* Reading "Introduction to Cloud Computing" by Timothy Chou.<br />
<br />
= Fall 2011 =<br />
* Internship<br />
<br />
= Summer 2011 (RA) =<br />
* Courses: <br />
**CMPT826 (dropped)<br />
<br />
===June 14===<br />
* New results added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4496Private:progress-khodabakhshi2011-06-15T02:43:43Z<p>Nkhodaba: </p>
<hr />
<div>= Summer 2011 (RA) =<br />
* Courses:<br />
<br />
===June 14===<br />
* New results added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4495Private:progress-khodabakhshi2011-06-15T02:43:03Z<p>Nkhodaba: </p>
<hr />
<div>= Summer 2011 (RA) =<br />
* Courses:<br />
**CMPT 826: Automated Learning Reasoning<br />
<br />
===June 14===<br />
* New results added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4478Private:progress-khodabakhshi2011-06-01T03:41:59Z<p>Nkhodaba: </p>
<hr />
<div>= Summer 2011 (RA) =<br />
* Courses:<br />
**CMPT 826: Automated Learning Reasoning<br />
<br />
===May 31===<br />
* Implementation part added to [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report].<br />
* Normalization of the score changed and the plot of the new normalized score are updated in the report. <br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4453Private:progress-khodabakhshi2011-05-18T15:45:45Z<p>Nkhodaba: </p>
<hr />
<div>= Summer 2011 (RA) =<br />
* Courses:<br />
**CMPT 826: Automated Learning Reasoning<br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
:* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
:* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4452Private:progress-khodabakhshi2011-05-18T15:45:18Z<p>Nkhodaba: </p>
<hr />
<div>= Summer 2011 (RA) =<br />
* Courses:<br />
**CMPT 826: Automated Learning Reasoning<br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
:* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
:* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
:* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4451Private:progress-khodabakhshi2011-05-18T15:39:13Z<p>Nkhodaba: </p>
<hr />
<div>= Summer 2011 (RA) =<br />
* Courses:<br />
**CMPT 826: Automated Learning Reasoning<br />
<br />
===May 17===<br />
* Reading this paper "Model-Based Joint Bit Allocation Between Texture videos and Depth Maps for 3D Video Coding". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree.<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4450Private:progress-khodabakhshi2011-05-18T15:36:00Z<p>Nkhodaba: </p>
<hr />
<div>= Summer 2011 (RA) =<br />
* Courses:<br />
**CMPT 826: Automated Learning Reasoning<br />
<br />
===May 17===<br />
* Reading this paper "". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4449Private:progress-khodabakhshi2011-05-18T15:34:19Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 17===<br />
* Reading this paper "". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
* Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
* and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
* Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
* Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
* Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4448Private:progress-khodabakhshi2011-05-18T15:31:35Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 17===<br />
* Reading this paper "". Motivation: to see how distorted a synthesized view would be if its texture and depth are distorted to some degree<br />
<br />
* Working on the normalization of the scores, and defining a threshold. So that if the score between two videos are greater than this threshold, they are considered a copy of each other. After defining this threshold, precision and recall of the system can be determined.<br />
<br />
- Probably I will try a sigmoid function to normalize the scores between [0,1]<br />
- and boost the score of the best matching video, if the first best matching video has a much higher relevance score than the second best matching video. x1 = x1 * (x1/x2)<br />
<br />
* What should be done next:<br />
- Right now the system uses all the frames of the videos, next step would be to use boundary detection algorithm to extract keyframes.<br />
- Right now I evaluated the performance of the system against view interpolation attack by using actual videos taken from different viewpoints by cameras. Next step would be to synthesize views and the use the synthesized ones and determine their distortion and use them for evaluation.<br />
- Right now the implementation and evaluation are considering 3D videos consist of one video + its depth. This can be extended to Multiview + Depth. If so, the depth extraction is need.<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4429Private:progress-khodabakhshi2011-05-10T05:58:31Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===May 9===<br />
* Evaluation part of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] has been updated<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4403Private:progress-khodabakhshi2011-04-26T21:58:27Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth results to make a better decision.<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4402Private:progress-khodabakhshi2011-04-26T21:57:52Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===April 26===<br />
* Implementing: Combining SIFT and Depth result<br />
* Next step would be to evaluate it. Different transformations must be applied to query videos and robustness of the system against them should be measured. <br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4394Private:progress-khodabakhshi2011-04-19T07:31:07Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===April 18===<br />
* Course work (final exam)<br />
* The "D. Depth map creation for multiview video" section of my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is updated.<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4348Private:progress-khodabakhshi2011-04-09T08:11:02Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===April 8===<br />
* Course work (problem set + presentation)<br />
* Exploring depth extraction details<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4327Private:progress-khodabakhshi2011-03-30T20:45:53Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===March 29===<br />
* Implementing the depth signature part of the system. The updated [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 8===<br />
* Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4259Private:progress-khodabakhshi2011-03-08T16:29:04Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===March 8===<br />
*Exploring multiview geometry and depth extraction methods. My [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] is here.<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4238Private:progress-khodabakhshi2011-03-01T08:14:34Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I am implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk] using the mentioned libraries. The implementation up to and including frame level matching phase is completed till now.<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4237Private:progress-khodabakhshi2011-03-01T08:03:07Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===March 1===<br />
* Continuing implementation<br />
I have started implementing the proposed algorithm in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx talk].<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4236Private:progress-khodabakhshi2011-03-01T07:42:13Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===March 1===<br />
* Continuing implementation<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use these two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4235Private:progress-khodabakhshi2011-03-01T07:41:35Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===March 1===<br />
* Continuing implementation<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. The first one is by author of the SIFT, David Lowe. However, his implementation is not open source, and he just distributed a binary file. In other words, this implementation is not flexible and it's not possible to change its parameters, which is necessary in our task, since we have to change its parameters to reduce the number of SIFT features by accepting the most informative ones. The implementation that I decided to use is [http://www.vlfeat.org/ one] by Andrea Vedaldi, which is in C language, and has Matlab interface as well. The Open-Source SIFT Library won first place at the [http://www.acmmm10.org/2010/10/open-source-software-competition-winners/ ACM Multimedia 2010 Open-Source Software Competition] (the competition was stiff). It is flexible enough for our task. The two parameters that we need to change are the peak threshold, and the edge threshold, which can be change using this library.<br />
<br />
For the approximate nearest neighbor task, I have decided to use open source [http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN FLANN] library, which is one of the fastest nearest neighbor algorithms, as I have explained in more details in my [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report]. This library is in C++ language, and also have Matlab interface as well.<br />
<br />
I have learned to use this two libraries using their Matlab interface. The reason is that this task needs some kind of matrix manipulation, and Matlab is efficient in this case.<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4234Private:progress-khodabakhshi2011-03-01T06:49:15Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===March 1===<br />
* Continuing implementation<br />
<br />
===Feb 22===<br />
* Continuing implementation<br />
There are some reliable implementation of SIFT algorithm. <br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=People&diff=4219People2011-02-28T04:22:58Z<p>Nkhodaba: </p>
<hr />
<div>==Faculty ==<br />
<br />
* [http://www.cs.sfu.ca/~mhefeeda/ Mohamed Hefeeda]<br />
<br />
* [http://www.cs.sfu.ca/~peters/ Joseph G. Peters]<br />
<br />
<br/><br />
<center><br />
{| border="0"<br />
|[[Image:Mhefeeda.jpg|center|Mohamed Hefeeda|100px]]<br />
|[[Image:Peters.jpg|center|Joseph Peters|100px]]<br />
|-<br />
|align="center" width="200pt"|Mohamed Hefeeda<br />
|align="center" width="200pt"|Joseph G. Peters<br />
|}<br />
</center><br />
<br />
== Current Students ==<br />
<br />
{| border="0"<br />
|width="500pt"|<br />
* [http://www.sfu.ca/~aah10/ Ahmed Hamza, Ph.D.]<br />
|[ [[Private:progress-hamza|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* Saleh Almowuena, Ph.D.<br />
|[ [[Private:progress-almowuena|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* Mohammad Alkurbi, M.Sc.<br />
|[ [[Private:progress-alkurbi|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* [http://www.cs.sfu.ca/~fma20/personal/ Farid Molazem Tabrizi, M.Sc.] (co-supervised with Prof. Joesph Peters)<br />
|[ [[Private:progress-tabrizi|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* Cameron Harvey, M.Sc.<br />
|[ [[Private:progress-harvey|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* [http://www.cs.sfu.ca/~hsadeghi/personal/ Hamed Sadeghi Neshat, M.Sc.]<br />
|[ [[Private:progress-neshat|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* Fei (Jeffrey) Gao, M.Sc.<br />
|[ [[Private:progress-gao|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* [http://www.sfu.ca/~tdameh/ Taher Dameh, M.Sc.]<br />
|[ [[Private:progress-dameh|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* Bassam Almohammadi, M.Sc.<br />
|[ [[Private:progress-almohammadi|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* Azin Dastpak, M.Sc. (co-supervised with Prof. Jiangchuan Liu)<br />
|[ [[Private:progress-dastpak|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* Kaushik Choudhary, M.Sc.<br />
|[ [[Private:progress-choudhary|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* Mathieu Spénard, M.Sc.<br />
|[ [[Private:progress-spenard|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* Naghmeh Khodabakhshi, M.Sc.<br />
|[ [[Private:progress-khodabakhshi|Progress]] ]<br />
|-<br />
|width="500pt"|<br />
* Ahmed Bu-khamsin, M.Sc.<br />
|[ [[Private:progress-bu-khamsin|Progress]] ]<br />
|}<br />
<br />
<br />
<br />
<br/><br />
<center><br />
{| border="0"<br />
|[[Image:Ahamza.JPG|center|Ahmed Hamza|80x100px]]<br />
|[[Image:saleh_small.jpg|center|Saleh Almowuena|80x100px]]<br />
|[[Image:Mohammad.jpg|center|Mohammad Alkurbi|80x100px]]<br />
|[[Image:Farid.jpg|center|Farid Tabrizi|80x100px]]<br />
|-<br />
|align="center" align="center" width="100pt"|Ahmed Hamza<br />
|align="center" align="center" width="100pt"|Saleh Almowuena<br />
|align="center" align="center" width="100pt"|Mohammad Alkurbi<br />
|align="center" align="center" width="100pt"|Farid Tabrizi<br />
|}<br />
{| border="0"<br />
|[[Image:Cameron.jpg|center|Cameron Harvey|80x100px]]<br />
|[[Image:Hamed.jpg|center|Hamed SadeghiNeshat|80x100px]]<br />
|[[Image:Fei.jpg|center|Fei Gao|80x100px]]<br />
|[[Image:Taher.jpg|center|Taher Dameh|80x100px]]<br />
|[[Image:Bassam.jpg|center|Bassam Almohammadi|80x100px]]<br />
|-<br />
|align="center" align="center" width="100pt"|Cameron Harvey<br />
|align="center" align="center" width="100pt"|Hamed<br/>SadeghiNeshat<br />
|align="center" align="center" width="100pt"|Fei Gao<br />
|align="center" align="center" width="100pt"|Taher Dameh<br />
|align="center" align="center" width="100pt"|Bassam Almohammadi<br />
|}<br />
{| border="0"<br />
|[[Image:Azin.jpg|center|Azin Dastpak|80x100px]]<br />
|[[Image:Kaushik.jpg|center|Kaushik Choudhary|80x100px]]<br />
|[[Image:Mathieu.jpg|center|Mathieu Spénard|80x120px]]<br />
|[[Image:Naghmeh.jpg|center|Naghmeh Khodabakhshi|80x100px]]<br />
|[[Image:AhmedBuKhamsin.jpg|center|Ahmed Bu-khamsin|80x100px]]<br />
<br />
|-<br />
|align="center" align="center" width="100pt"|Azin Dastpak<br />
|align="center" align="center" width="100pt"|Kaushik Choudhary<br />
|align="center" align="center" width="100pt"|Mathieu Spénard<br />
|align="center" align="center" width="100pt"|Naghmeh Khodabakhshi<br />
|align="center" align="center" width="100pt"|Ahmed Bu-khamsin<br />
<br />
|}<br />
</center><br />
<br />
<br />
== Visitors ==<br />
<br />
* Gordon Leung, Undergraduate (NSERC USRA, Summer 2010)<br />
<br />
* Andreas Berger, Graduate (Research Visitor from The Telecommunications Research Center Vienna, Feb -- May 2009)<br />
<br />
* Vikas Kumar, Undergraduate (Research Internship, May -- July 2008) <br />
<br />
* Nitin Chiluka, Undergraduate (Research Internship, December 2007 -- May 2008)<br />
<br />
* Nicolas Gomez, Undergraduate (NSERC USRA, Summer 2007)<br />
<br />
* Pouya Alagheband, Undergraduate (NSERC USRA, Summer 2007)<br />
<br />
<br />
== Graduated Students ==<br />
<br />
<br />
'''Ph.D. Students'''<br />
<br />
* ChengHsin Hsu, Ph.D., Fall 2009, [http://nsl.cs.surrey.sfu.ca/theses/hsu09.pdf Efficient Mobile Multimedia Streaming]. First Job: Senior Researcher, Deutsche Telekom R&D Lab, California, USA. <br />
<br />
<br />
'''M.Sc. Students -- Thesis Option (thesis = 15 credits)'''<br />
<br />
* Shabnam Mirshokraie, M.Sc., Fall 2010, [http://nsl.cs.surrey.sfu.ca/theses/mirshokraie10.pdf Live Peer-to-Peer Streaming with Scalable Video Coding and Network Coding]<br />
<br />
* Somsubhra Sharangi, M.Sc., Fall 2010, [http://nsl.cs.surrey.sfu.ca/theses/sharangi10.pdf Scalable Video Streaming over WiMAX Networks] (co-supervised with Prof. Ramesh Krishnamurti)|[ [[Private:progress-sharangi|Progress]] ]<br />
<br />
* Yuanbin Shen, M.Sc., Summer 2010, [http://nsl.cs.surrey.sfu.ca/theses/shen10.pdf Efficient Algorithms for Multi-sender Data Transmission in Swarm-based Peer-to-peer Streaming Systems]<br />
<br />
* Cong Ly, M.Sc., Summer 2010, [http://nsl.cs.surrey.sfu.ca/theses/ly10.pdf Latency Reduction in Online Multiplayer Games Using Detour Routing]<br />
<br />
* Yi Liu, M.Sc., Fall 2009, [http://nsl.cs.surrey.sfu.ca/theses/liu09.pdf Video Streaming over Cooperative Wireless Networks]<br />
<br />
* Greg Kowalski, M.Sc., Fall 2009, [http://nsl.cs.surrey.sfu.ca/theses/kowalski09.pdf Empirical Analysis of Multi-Sender Segment Transmission Algorithms in Peer-to-Peer Streaming]<br />
<br />
* Kianoosh Mokhtarian, M.Sc., Fall 2009, [http://nsl.cs.surrey.sfu.ca/theses/mokhtarian09.pdf Efficient and Secure Delivery of Scalable Video Streams]<br />
<br />
* Behrooz Noorizadeh, M.Sc., Fall 2007, [http://nsl.cs.surrey.sfu.ca/theses/noorizadeh07.pdf Cooperative Proxy Caching for Peer-to-Peer Traffic]<br />
<br />
* Hossein Ahmadi, M.Sc., Summer 2007, [http://nsl.cs.surrey.sfu.ca/theses/ahmadi07.pdf Probabilistic Coverage and Connectivity in Wireless Sensor Networks]<br />
<br />
* Majid Bagheri, M.Sc., Summer 2007, [http://nsl.cs.surrey.sfu.ca/theses/bagheri07.pdf Efficient K-Coverage Algorithms for Wireless Sensor Networks and their Applications to Early Detection of Forest Fires]<br />
<br />
* Osama Saleh, M.Sc., Fall 2006 [http://nsl.cs.surrey.sfu.ca/theses/saleh06.pdf Modeling and Caching of Peer-to-Peer Traffic]<br />
<br />
<br />
<br/><br />
<center><br />
{| border="0"<br />
|[[Image:Shabnam.jpg|center|Shabnam Mirshokraie|80x100px]]<br />
|[[Image:Som.JPG|center|Somsubhra Sharangi|80x100px]]<br />
|-<br />
|align="center" align="center" width="100pt"|Shabnam<br/>Mirshokraie<br />
|align="center" align="center" width="100pt"|Somsubhra Sharangi<br />
|}<br />
{| border="0"<br />
|[[Image:Yuanbin.jpg|center|Yuanbin Shen|80x100px]]<br />
|[[Image:Cong.jpg|center|Cong Ly|80x100px]]<br />
|[[Image:Cheng.JPG|center|ChengHsin Hsu|80x100px]]<br />
|[[Image:Liuyi.jpg|center|Yi Liu|80x100px]]<br />
|[[Image:Greg.jpg|center|Greg Kowalski|80x100px]]<br />
|-<br />
|align="center" align="center" width="100pt"|Yuanbin Shen<br />
|align="center" width="100pt"|Cong Ly<br />
|align="center" width="100pt"|ChengHsin Hsu<br />
|align="center" width="100pt"|Yi Liu<br />
|align="center" width="100pt"|Greg Kowalski<br />
|}<br />
{| border="0"<br />
|[[Image:Kianoosh.jpg|center|Kianoosh Mokhtarian|80x100px]]<br />
|[[Image:Behrooz.jpg|center|Behrooz Noorizadeh|80x100px]]<br />
|[[Image:Ahmadi.jpg|center|Hossein Ahmadi|80x100px]]<br />
|[[Image:Mbagheri.jpg|center|Majid Bagheri|80x100px]]<br />
|[[Image:Saleh.jpg|center|Osama Saleh|80x100px]]<br />
|-<br />
|align="center" width="100pt"|Kianoosh Mokhtarian<br />
|align="center" width="100pt"|Behrooz<br/>Noorizadeh<br />
|align="center" width="100pt"|Hossein Ahmadi<br />
|align="center" width="100pt"|Majid Bagheri<br />
|align="center" width="100pt"|Osama Saleh<br />
|}<br />
<br />
</center><br />
<br />
== Contacts == <br />
<br />
* [[Private:contacts|List of contact persons in academia and industry (Login Required). ]]</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=File:Naghmeh.jpg&diff=4218File:Naghmeh.jpg2011-02-28T04:15:06Z<p>Nkhodaba: </p>
<hr />
<div></div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4204Private:progress-khodabakhshi2011-02-16T18:52:00Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===Feb 15===<br />
* Starting implementation<br />
<br />
===Feb 8===<br />
* Exploring different nearest neighbor techniques in high dimensional spaces<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=group_meeting&diff=4201group meeting2011-02-15T02:58:14Z<p>Nkhodaba: </p>
<hr />
<div>We hold regular meetings for discussion and for every student to update the group on his/her progress. In some of the meetings, graduate students present talks summarizing their research progress so far. <br />
<br />
The meetings are good opportunities for students to practice their presentation skills and to get constructive feedback from the group on their research. The meetings keep the group members informed about different research problems being addressed in the group. They are also very helpful in finding research topics specially for new students. <br />
<br />
Everybody is welcome to attend. Meeting time: Every Tuesday, 10:00 AM -12:00 PM, room SUR 4010. <br />
<br />
<br />
== Spring 2011==<br />
<br />
* 1 Feb: Ahmed Bu-khamsin, Top Ten Computationally-Complex Problems in Oil and Gas Exploration Filed<br />
<br />
* 25 Jan: Naghmeh, [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx 3D Video Copy Detection]<br />
<br />
* 18 Jan: Cameron, [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/harvey/talks/Copy%20Detection%20Using%20Optical%20Flow.pptx Video Copy Detection using Optical Flow]<br />
<br />
* 11 Jan: Mathieu, [[media:3D_VideosOverview.pptx | 3D Media - An Overview]]<br />
<br />
<br />
<br />
Group meetings were held biweekly up to Dec 2010. <br />
<br />
== Fall 2010==<br />
<br />
* 21 Dec 10: Group discussion.<br />
<br />
* 9 Dec 10: Mohammad, [[media:Botnet-Detection-2.0.pptx | Detection of SIP Botnets Based on C&C Communication]]<br />
<br />
* 23 Nov 10: Taher, Approximation algorithms for Web-Scale Kernel Methods<br />
<br />
* 19 Oct 10: Jeff, [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/gao/talks/LSH_Cluster.pdf Gram Matrix Approximation Using Locality Sensitive Hashing on Cluster]<br />
<br />
* 7 Oct 10: Dr. Rocky Chang (Hong Kong Polytechnic University),<br/> [[media:Rocky-SFU-7-Oct-2010.pdf | Active Measurement of Data-Path Quality in a Non-cooperative Internet]]<br />
<br />
* 28 Sep 10: Ahmed, [[media:DRS.pdf | Energy-Efficient Gaming on Mobile Devices using Dead Reckoning-based Power Management]]<br />
<br />
<br />
== Spring/Summer 2010==<br />
<br />
* 31 Aug 10: Hamed, [[media:Predicting_Click_Through_Rate_for_new_ads.pdf | Predicting Click Through Rate for New Ads with Semantically Similarity Measurement]]<br />
<br />
* 9 Aug 10: Yuanbin, [[media:mutisendP2Pstream.pdf | Efficient Algorithms for Multi-Sender Data Transmission in Swarm-based P2P Streaming Systems]]<br />
<br />
* 3 Aug 10: Azin, [[media:CognitiveRadio.ppt | Cognitive Radio Networks]]<br />
<br />
* 20 July 10: Farid, [[media:movid10.pdf | Optimal Scalable Video Multiplexing in Mobile Broadcast Networks]]<br />
<br />
* 17 May 10: Cameron, Reducing Energy Consumption in Online Network Games on Mobile Devices<br />
<br />
* 10 May 10: Cong, Latency Reduction in Online Network Games<br />
<br />
* 19 April 10: Shabnam, [[media:Svc-nc.ppt | Live P2P Streaming with Scalable Video Coding and Network Coding]]<br />
<br />
* 29 March 10: Jeff and Taher, [[media:AppAlgo.ppt | Approximation algorithms for Kernel Methods on Multi-core CPUs and GPUs]]<br />
<br />
* 15 March 10: Som, [http://www.cs.sfu.ca/~ssa121/personal/wimaxSVC.pdf Video Streaming over WiMAX]<br />
<br />
* 1 March 10: Farid, [[media:scalable_video_streaming_for_mobiletv.pptx | Scalable Video Streaming for MobileTV]]<br />
<br />
* 1 Feb 10: Ahmed, [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/hamza/talks/pCDN_SVC/pCDN_SVC.pdf Design of pCDN with Scalable Video Coding]<br />
<br />
* 18 Jan 10: Shabnam, P2P Streaming with Newtork Coding and Scalable Video Coding<br />
<br />
<br />
== Fall 2009==<br />
<br />
* 8 December 09: Yi, Video Streaming over Cooperative Wireless Networks<br />
<br />
* 10 Nov 09: Cheng, [[media:testbed.ppt | Design of a Mobile TV Testbed]]<br />
<br />
* 27 October 09: Yuanbin, Segment Scheduling in P2P Streaming Systems<br />
<br />
* 13 October 09: Ahmed, [[media:LTE.pdf | Long Term Evolution (LTE) - A Tutorial]]<br />
<br />
* 6 October 09: Cheng, [[media:Mm09.ppt | Statistical Multiplexing of VBR Video Streams]] (ACM MM 09 talk)<br />
<br />
* 22 September 09: Som, Video Streaming over WiMAX Networks<br />
<br />
* 8 September 09: Cong, Minimizing Round-Trip Time in Online Games<br />
<br />
<br />
== Summer 2009==<br />
<br />
* 18 August 09: Mohammad and Cong: 30 min each. Present their Directed Reading projects. <br />
<br />
* 14 July 09: Cheng, [[media:wimaxTV.pptx | Broadcasting Variable-Bit-Rate Videos in 802.16e-Like Mobile Networks]] <br />
<br />
* 7 July 09: Yi<br />
<br />
* 26 June 09: Ahmed <br />
<br />
* 5 June 09: '''Canceled''' (Mohamed attending NOSSDAV'09)<br />
<br />
* 29 May 09: Kianoosh, End-to-End Secure Delivery of Scalable Video Streams <br />
<br />
* 22 May 09: Cong, [[media:wimax.pptx| Multimedia Streaming over WiMAX Networks]]<br />
<br />
* 8 May 09: Kianoosh, Analysis of Authentication Schemes for Nonscalable Video Streams<br />
<br />
<br />
== Spring 2009 ==<br />
<br />
* 17 Apr 09: [[media:infocom09.pptx|Cheng (practice your infocom presentation)]]<br />
<br />
* 27 March 09: Andreas Berger, [[media:Nsl_vancouver.odp | Network-based Detection of SIP Bots]]<br />
<br />
* 27 Feb 09: Shabnam and Yuanbin<br />
<br />
* 23 Jan 09: Cheng (rehearse your PhD proposal) and Kianoosh</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4156Private:progress-khodabakhshi2011-02-04T09:29:33Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4155Private:progress-khodabakhshi2011-02-04T09:28:56Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/talks/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4154Private:progress-khodabakhshi2011-02-04T09:26:45Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4153Private:progress-khodabakhshi2011-02-02T20:58:56Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protocols<br />
<br />
===Feb 1===<br />
* Exploring depth maps features<br />
<br />
===Jan 24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate2.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4143Private:progress-khodabakhshi2011-01-30T00:17:45Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protcols<br />
<br />
===Jan24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/3DVideoCopyDetection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate2.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4142Private:progress-khodabakhshi2011-01-29T03:49:09Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protcols<br />
<br />
===Jan24===<br />
* Adapting 2D CBVCD to 3D<br />
* Preparing the group meeting talk: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/3D Video Copy Detection.pptx Slides].<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate2.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodabahttps://nmsl.cs.sfu.ca/index.php?title=Private:progress-khodabakhshi&diff=4091Private:progress-khodabakhshi2011-01-25T00:24:15Z<p>Nkhodaba: </p>
<hr />
<div>= Spring 2011 (RA) =<br />
* Courses:<br />
**CMPT 771: Internet Architecture and Protcols<br />
<br />
===Jan 17===<br />
* Exploring image registration methods<br />
* Exploring feature-based image registration methods<br />
* Exploring feature-based image registration methods that use SIFT-based methods<br />
* A more detailed report is available at: [https://cs-nsl-svn.cs.surrey.sfu.ca/cssvn/nsl-members/khodabakhshi/reports/3-1-11/reportTemplate2.pdf report] but it is still changing...<br />
<br />
=== Jan 10 ===<br />
* Exploring 3D videos.<br />
* Exploring literature for 3D video copy detection<br />
<br />
=== Jan 3 ===<br />
* having fun, not really working :)<br />
<br />
= Fall 2010 (TA) =<br />
* Courses:<br />
**CMPT 701: Design/Analysis Algorithms<br />
**CMPT 820: Multimedia Systems<br />
<br />
<br />
* Worked on 2D video copy detection.</div>Nkhodaba