Network-Adaptive Video Communication Using Packet Path Diversity and Rate-Distortion Optimized Reference Picture Selection

Authors:
Yi J. Liang;Eric Setton;Bernd Girod
Affiliations:
Information Systems Laboratory, Department of Electrical Engineering, Stanford University, Stanford, USA 94305;Information Systems Laboratory, Department of Electrical Engineering, Stanford University, Stanford, USA 94305;Information Systems Laboratory, Department of Electrical Engineering, Stanford University, Stanford, USA 94305
Venue:
Journal of VLSI Signal Processing Systems
Year:
2005

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Abstract

In this paper, we present error-resilient Internet video transmission using path diversity and rate-distortion optimized reference picture selection. Under this scheme, the optimal packet dependency is determined adapting to network characteristics and video content, to achieve a better trade-off between coding efficiency and forming independent streams to increase error-resilience. The optimization is achieved within a rate-distortion framework, so that the expected end-to-end distortion is minimized under the given rate constraint. The expected distortion is calculated based on an accurate binary tree modeling with the effects of channel loss and error concealment taken into account. With the aid of active probing, packets are sent across multiple available paths according to a transmission policy which takes advantage of path diversity and seeks to minimize the loss rate. Experiments demonstrate that the proposed scheme provides significant diversity gain, as well as gains over video redundancy coding and the NACK mode of conventional reference picture selection.