Video quality estimation in wireless IP networks: Algorithms and applications
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Rate-distortion optimized frame dropping for multiuser streaming and conversational videos
Advances in Multimedia
Middleware abstractions for cross-layer controlled media streaming
Proceedings of the 2nd workshop on Middleware-application interaction: affiliated with the DisCoTec federated conferences 2008
Modeling and analysis of distortion caused by Markov-model burst packet losses in video transmission
IEEE Transactions on Circuits and Systems for Video Technology
Generalized butterfly graph and its application to video stream authentication
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Multimedia
Rate-distortion optimized scheduling for redundant video representation
IEEE Transactions on Image Processing
Loss-distortion estimation for practical H.264/AVC streams
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
A versatile model for packet loss visibility and its application to packet prioritization
IEEE Transactions on Image Processing
Server-Aided Adaptive Live Video Streaming Over P2P Networks
Journal of Signal Processing Systems
RD-optimized interactive streaming of multiview video with multiple encodings
Journal of Visual Communication and Image Representation
Visual relevance evaluation using rate distortion analysis in the circular harmonic functions domain
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Adaptation strategies for MGS scalable video streaming
Image Communication
A cost-effective cloud computing framework for accelerating multimedia communication simulations
Journal of Parallel and Distributed Computing
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We present a technique for low-complexity rate-distortion (R-D) optimized adaptive video streaming based on the concept of rate-distortion hint track (RDHT). RDHTs store the precomputed characteristics of a compressed media source that are crucial for high performance online streaming but difficult to compute in real time. This enables low-complexity adaptation to variations in transport conditions such as available data rate or packet loss. An RDHT-based streaming system has three components: 1) information that summarizes the R-D attributes of the media; 2) an algorithm for using the RDHT to predict the distortion for a feasible packet schedule; and 3) a method for determining the best packet schedule to adapt the streaming to the communication channel. A family of distortion models, denoted distortion chains, are presented which accurately predict the distortion produced by arbitrary packet loss patterns. Two distortion chain models are examined which lead to two RDHT-based techniques. We evaluate the proposed techniques for two canonical problems in streaming media, adaptation to available data rate and to packet loss. Experimental results demonstrate that for the difficult case of nonscalably coded H.264 video, the proposed systems provide significant performance gains over conventional low-complexity streaming systems, and achieve this gain with a comparable level of complexity making them suitable for online R-D optimized streaming.