We examine and model the bit rate variability-distortion (VD) curve of MPEG–4 Part 2 VBR video encodings, which has applications for optimal statistical multiplexing of low bit rate streaming video. We show that the concave VD curve shape at high compression ratios or large quantization scales, is influenced by both the texture and the motion information. We use linear and quadratic models for the texture and motion bits statistics and devise accurate VD curve models. The model parameters are obtained from statistics that are estimated from two encodings. This work extends our previous work on piecewise models of the VD curve. The texture and motion based VD model based on two encodings has comparable accuracy to a piecewise model based on three encodings. In addition, the texture and motion based VD model provides fundamental insights into how texture and motion affects traffic variability
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