Channel Distortion Analysis And Modeling For Multi-view 3d Video Transmission Over IP Networks

In packet-switched networks, packets may be discarded due to buffer overflow at intermediate nodes of the network, or may be considered lost due to long queuing delays. Moreover, compressed video signals, especially coded stereoscopic video sequences, are extremely vulnerable to transmission errors, since low bit-rate video coding schemes rely on inter-frame predictive coding to achieve high coding efficiency. The coding structure of motion-compensated inter-frame prediction creates strong spatio-temporal dependency in video frames. Consequently, unavoidable packet losses during transmission may result in catastrophic error propagation and thus severe quality degradation at the decoder side. To understand the effect of packet loss on video quality,it is desired to model the end-to-end distortion caused by packet loss in decoded video. Modeling the effect of packet losses on the end-to-end video quality is important for jointly determining parameters for source coding (e.g., quantisation and intra-rate), rate-distortion optimisation, channel code rate control, and inter-/intra-mode switching.Channel distortion modeling for generic multi-view video transmission remains a unfilled blank, despite that intensive research efforts have been devoted to model traditional 2-D video transmission.This paper aims to fill this blank through developing a recursive distortion model for multi-view video transmission over lossy packet-switched networks. Based on the study on the characteristics of multi-view video coding and the propagating behavior of transmission error due to random frame losses, a recursive mathematical model is derived to estimate the expected channel-induced distortion at both the frame and sequence levels. The model we develop explicitly considers both temporal and inter-view dependencies, induced by motion-compensated and disparity-compensated coding, respectively. The derived model is applicable to all multi-view video encoders using the classical block-based motion-/disparity-compensated prediction framework. It is capable of handling sophisticated two-dimensional error propagation and markedly reduce the modeling complexity while still achieving high accuracy.In addition to theoretical analyses, both objective and subjective evaluation results are presented to compare the modeled and measured distortion results, which clearly demonstrate that the developed model is able to estimate the expected channel distortions at both the frame and GGoP levels with high accuracy. Therefore, in practical applications, our distortion model can be employed to study the performance of frame-based error resilient techniques for MVV transmission over packet-switched networks. Finally, based on the study on distortion estimation model, an error concealment scheme for multi-view stereo video is exploited in this transport system, in order to solve the packet loss problem in IP networks.