Difference between revisions of "Content-Aware Adaptive Streaming"
From NMSL
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* Using only HS histogram could help reduce the dimension. | * Using only HS histogram could help reduce the dimension. | ||
* Explore video quality measures | * Explore video quality measures | ||
| + | * The feature space idea can be used to design a new quality metric. Frames from the original and the scaled sequence are mapped to a lower dimension and the distance is measured. | ||
* [[Private:Surveillance|Surveillance (Login Required)]] | * [[Private:Surveillance|Surveillance (Login Required)]] | ||
Revision as of 11:03, 1 April 2008
We are designing adaptive streaming algorithms that are based on the visual content of the video streams. The goal is to adaptively transmit the most important frames to clients to yield the best quality. Several ideas are being explored, including: real time and offline processing of video streams, summarization of sports videos, and adaptation of multi-layer scalable video streams.
People
- Mohamed Hefeeda (Assistant Professor)
- Wael Abd-Almageed (Assistant Research Scientist at UMD)
- Majid Bagheri (PhD Student)
Discussion and Ideas
- discussion_25mar08.pdf
- discussion_17mar08.pdf
- Using only HS histogram could help reduce the dimension.
- Explore video quality measures
- The feature space idea can be used to design a new quality metric. Frames from the original and the scaled sequence are mapped to a lower dimension and the distance is measured.
- Surveillance (Login Required)
References and Links
- Y. Gong and X. Liu, Video summarization using singular value decomposition, in Proc. of IEEE Conference on Computer Vision and Pattern Recognition, Hilton Head Island, SC, June 2000, pp. 174–180.
- K. Tan, R. Ribier, S. Liou, Content-sensitive video streaming over low bitrate and lossy wireless network, ACM Multimedia 2001.
- X. Zhou, S. Liou, Optimal nonlinear sampling for video streaming at low bit rates, IEEE Transactions on Circuits and Systems for Video Technology, Jun 2002, 12(6), pp. 535-544.
