Content-Aware Adaptive Streaming

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 feature space dimension
• Explore video quality measures
• Feature extraction 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
• Online Summary Generator (submit a video, get the summary)
• investigate MPEG CLD and MAD features
• Initial Results on Video Summarization (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.

• ITU-T Tutorial: Objective perceptual assessment of video quality: Full reference television, International Telecommunication Union, Geneva, Switzerland, 2004.

• ITU-R Recommendation BT.500-11: Methodology for the subjective assessment of the quality of television pictures, International Telecommunication Union, Geneva, Switzerland, 2002.