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- W161201892 abstract "We are presenting a new framework of content based video (CBV) modeling, suitable for scalable variable bit rate (VBR) video traffic. Our approach differs form previous works in that it is not based only on matching of various statistics of the original source, but rather it includes characterization and classification of the video content. We show, that CBV model is fully compatible with existing compression algorithms and also with the current research directions in the very low bit rate video compression. As an example, we introduce MPEG-2 VBR video traffic model based on the ordered list of scene descriptors forming the template of the video stream. The model is verified in terms of trace, first and second order statistics. Results of simulation of ATM network interface multiplexer indicate that the CBV model can generate video traffic which closely matches the important performance parameters and statistics of real VBR MPEG-2 stream. Based on our results we argue that introduction of video content into the modeling of video streams allows us to specify the different classes of important features of video sources resulting in more accurate VBR video traffic model. The CBV model is able to generate the VBR traffic with specific video content and therefore it can be successfully used in the performance estimation and simulation of storage retrieval, buffering, scheduling and admission control of video servers and networks." @default.
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- W161201892 modified "2023-09-26" @default.
- W161201892 title "A Content Based Approach to VBR Video Source Modeling" @default.
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