Channel distortion modeling for multi-view video transmission over packet-switched networks

Abstract

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. Both objective and subjective experimental results are presented to demonstrate that the proposed model is capable of effectively model channel-induced distortion for multi-view video.