Soft ARQ for Layered Streaming Media
Journal of VLSI Signal Processing Systems - Special issue on multimedia signal processing
Rate-distortion Optimized Packet Scheduling and Routing for Media Streaming with Path Diversity
DCC '03 Proceedings of the Conference on Data Compression
Rate-distortion optimized streaming of packetized media
IEEE Transactions on Multimedia
The Virtue of Patience in Low-Complexity Scheduling of Packetized Media With Feedback
IEEE Transactions on Multimedia
Priority encoding transmission
IEEE Transactions on Information Theory - Part 1
Video coding with optimal inter/intra-mode switching for packet loss resilience
IEEE Journal on Selected Areas in Communications
Error resilience support in H.263+
IEEE Transactions on Circuits and Systems for Video Technology
Video coding for streaming media delivery on the Internet
IEEE Transactions on Circuits and Systems for Video Technology
Overview of fine granularity scalability in MPEG-4 video standard
IEEE Transactions on Circuits and Systems for Video Technology
Transactions letters. A rate-distortion optimal hybrid scalable/multipledescription video codec
IEEE Transactions on Circuits and Systems for Video Technology
Rate-distortion hint tracks for adaptive video streaming
IEEE Transactions on Circuits and Systems for Video Technology
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
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This paper extends rate-distortion optimized streaming techniques to operate on a general class of coding formats that explicitly support redundancy in their coding structure. Examples include multiple description layered coding (MDLC) and multiple independently encoded versions of a video source. Such source codecs usually produce multiple decoding paths, while previous work on video streaming has mostly focused on those encoding techniques that only generate a single decoding path. A new source model called Directed Acyclic HyperGraph is introduced to describe the dependency and redundancy relationship between different video data units with multiple decoding paths. Based on this model, we then propose two rate-distortion based packet scheduling algorithms, i.e., Lagrangian optimization and a greedy algorithm, to dynamically adjust the system's real-time redundancy to match the channel behavior. The proposed streaming system introduces two types of redundancies, namely, source redundancy and transport redundancy. This paper presents a detailed performance analysis of the individual benefits for error robustness provided by these redundancies and their interplay. Experimental results show that our proposed system with both redundancies achieves the best end-to-end performance on real-time video communication over a wide range of network scenarios.