Optimal quality adaptation for MPEG-4 fine-grained scalable video

Dynamic behavior of the Internet´s transmission resources makes it difficult to provide perceptually good quality of streaming video. MPEG-4 Fine-Grained Scalable coding is proposed to deal with this problem by distributing the data in enhancement layers over a wide range of bit rates. However, encoded video also exhibits significant data rate variability to provide a consistent quality video. We are, therefore, faced with the problem of trying to accommodate the mismatch between the available bandwidth variability and the encoded video variability. In this paper, we investigate quality adaptation of the layered VBR video generated by MPEG-4 FGS. Our goal is to develop a quality adaptation scheme that maximizes perceptual video quality through minimizing quality variation while at the same time increasing the usage of available bandwidth. We develop an optimal adaptation scheme and an online heuristic based on whether the network conditions are known a priori. Experimental results show that the online heuristic as well as the optimal adaptation algorithm provide consistent video quality when used over both TFRC and TCP.