Difference between revisions of "Private:progress-harvey"
From NMSL
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* '''Courses:''' None | * '''Courses:''' None | ||
'''working on: Video Copy Detection using Optical Flow ''' | '''working on: Video Copy Detection using Optical Flow ''' | ||
+ | |||
+ | ==== Feb 9 - Feb 15 ==== | ||
+ | * Worked on motion vector extraction using ffmpeg APIs | ||
+ | |||
==== Feb 2 - Feb 8 ==== | ==== Feb 2 - Feb 8 ==== | ||
* Downloaded and compiled ffprobe | * Downloaded and compiled ffprobe |
Revision as of 09:33, 15 February 2011
Spring 2011 (GF)
- Courses: None
working on: Video Copy Detection using Optical Flow
Feb 9 - Feb 15
- Worked on motion vector extraction using ffmpeg APIs
Feb 2 - Feb 8
- Downloaded and compiled ffprobe
- Started coding using ffmpeg libraries to extract I-frames and motion vectors. I have almost got the I-Frame portion worked out, and I will look into the motion vectors next week
Jan 19 - Feb 1
- Clustered SURF pts with both k-means and x-means
- Looking into how to extract I-frames and motion information from video sequences
- Downloaded and compiled source files for ffmpeg
- I think I can write something using this which will parse the mpegs
- I am having problems with permissions when i try to install - working with Ahmed and Jason
- Found a Matlab m-file for extracting motion vectors - I am not sure this will be all that usefulMatlab m files
- Also found a reworking of mplayer: modified mplayer (modified for flow)
- Janez Pers: The modifications are relatively minor, but ugly. The code that draws motion vectors is changed to dump the arrow directions and length into the text file. I cannot offer any support for compiling Mplayer though. The binary-only (windows) version is available here, it has added example video (it is better to start with this): windows binary. If you like the code and will use it in your scientific work, you can check my paper, which uses the same code for the second batch of experiments: Pers's paper.
- Short instructions:
- if you have MPEG4 already (I used the mpeg4 encoding as a fast way to get vectors as well), then skip the first step:
mencoder original.avi -ovc lavc -lavcopts vcodec=mpeg4 -o mpeg4encoded.avi
- now extract the motion vectors, without displaying the video (you can display the video as well, if you like, it was just more convenient for me)
mplayer mpeg4encoded.avi -benchmark -lavdopts vismv=1
- Now, the file opticalflow.dat will appear. Do not forget option vismv=1, the extraction is part of the visualisation.
- The file opticalflow.dat has the following format: framenum,x,y,vx,vy (vx vy being the vectors, x y being the position of the block).
- if you have MPEG4 already (I used the mpeg4 encoding as a fast way to get vectors as well), then skip the first step:
- Be aware that the data for the I frames will be missing (no flow there). And, in my experience, lower bitrates give better flow than high ones - with high ones the encoder does not need to bother with the motion vectors, since it has enough bandwith already...
Jan 19-25
- TrecVid 2008 final transformation document with examples: Transformation Document
- TrecVid 2008 explanation of how transformations are generated: Transformation Explanation
- 2010 TrecVid Requirements
- Downloaded the TrecVid 2007 and 2009 databases with test cases and testcases for 2010
- Downloaded and investigating x-means experimental software (Licensed to me for research purposes only)
- Experimenting with SURF interext points and x-means clustering
Jan 12-18
- Finished survey of Video Copy Detection methods Survey
- Prepared presentation on Optical Flow My Presentation
Jan 11
- Survey of State of the Art Techniques
Fall 2010 (RA)
- Courses:
- CMPT-820: Multimedia Systems
- worked on:
- Video Copy Detection
Summer 2010 (TA)
- Courses:
- None
- worked on:
- Energy-Efficient Gaming on Mobile Devices using Dead Reckoning-based Power Management
- submitted
- NetGames 2010: Energy-Efficient Gaming on Mobile Devices using Dead Reckoning-based Power Management (accepted)
Spring 2010 (RA)
- Courses:
- CMPT-822: Special topics in Database Systems
- CMPT 884: Computational Vision
- worked on:
- Energy-Efficient Gaming on Mobile Devices
- submitted
- Nosdav 2010: Energy-Efficient Gaming on Mobile Devices (not accepted)
Fall 2009 (TA)
- Courses:
- CMPT-705: Algorithm
- CMPT-771: Internet Architecture and Protocols