Abstract
We consider an error-resilient stereoscopic streaming system that uses an H.264-basedmultiview video codec and a rateless Raptor code for recovery from packet losses. One aim of the present work is to suggest a heuristic methodology for modeling the end-to-end rate-distortion (RD) characteristic of such a system. Another aim is to show how to make use of such a model to optimally select the parameters of the video codec and the Raptor code to minimize the overall distortion. Specifically, the proposed system models the RD curve of video encoder and performance of channel codec to jointly derive the optimal encoder bit rates and unequal error protection (UEP) rates specific to the layered stereoscopic video streaming.We define analytical RD curve modeling for each layer that includes the interdependency of these layers. A heuristic analytical model of the performance of Raptor codes is also defined. Furthermore, the distortion on the stereoscopic video quality caused by packet losses is estimated. Finally, analytical models and estimated single-packet loss distortions are used to minimize the end-to-end distortion and to obtain optimal encoder bit rates and UEP rates. The simulation results clearly demonstrate the significant quality gain against the nonoptimized schemes.
Highlights
The recent increase in interest for stereoscopic display systems and their growing deployment have spurred further research on efficient stereoscopic video streaming systems
We encode the stereoscopic videos with the bit rates obtained by the minimization in (21) for given pe and RC, and network abstraction layer (NAL) unit size is fixed to 150 bytes
We presented a rate-distortion optimized error-resilient stereoscopic video streaming system with Raptor codes and evaluated its performance via simulations
Summary
The recent increase in interest for stereoscopic display systems and their growing deployment have spurred further research on efficient stereoscopic video streaming systems. Stereoscopic video is formed by the simultaneous capture of two video sequences corresponding to the left and right views of human visual system, which increases the amount of source data. Existing stereoscopic techniques compress the data by exploiting the dependency between the left and right views; the compressed video is more sensitive to data losses and needs added protection against transmission errors. One faces a difficult joint source-channel coding problem, where the goal is to find the optimal balance between the distortion created by lossy source compression and the distortion caused by packet losses in the transmission channel. We address this problem by (i) proposing a heuristic methodology for modeling the end-toend RD characteristic of such a system, and (ii) dynamically adjusting the source compression ratio in response to channel conditions so as to minimize the overall distortion
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