View-Popularity-Driven Joint Source and Channel Coding of View and Rate Scalable Multi-View Video

摘要

We study the scenario of multicasting multi-view video content, recorded in the video plus depth format, to a collection of heterogeneous clients featuring Internet access links of diverse packet loss and transmission bandwidth values. We design a popularity-aware joint source-channel coding optimization framework that allocates source and channel coding rates to the captured content, such that the aggregate video quality of the reconstructed content across the client population is maximized, for the given packet loss and bandwidth characteristics of the clients and their view selection preferences. The source coding component of our framework features a procedure for generating a view and rate embedded bitstream that is optimally decodable at multiple data rates and accounts for the different popularity of diverse video perspectives of the scene of interest, among the clients. The channel coding component of our framework comprises an expanding-window rateless coding procedure that optimally allocates parity protection bits to the source encoded layers, in order to address packet loss across the unreliable client access links. We develop an optimization method that jointly computes the source and channel coding decisions of our framework, and also design a fast local-search-based solution that exhibits a negligible performance loss relative to the full optimization. We carry out comprehensive simulation experiments and demonstrate significant performance gains over competitive state-of-the-art methods (based on H.264/AVC and network coding, and H.264/SVC and our own channel coding procedure), across different scenario settings and parameter values.