Adaptation of variable-bit-rate compressed video for transport over a constant-bit-rate communication channel in broadband networks.

by Chi-yin Tse.Thesis (M.Phil.)--Chinese University of Hong Kong, 1995.Includes bibliographical references (leaves 118-[121]).Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Video Compression and Transport --- p.2Chapter 1.2 --- VBR-CBR Adaptation of Video Traffic --- p.5Chapter 1.3 --- Research Contributions --- p.7Chapter 1.3.1 --- Spatial Smoothing: Video Aggregation --- p.8Chapter 1.3.2 --- Temporal Smoothing: A Control-Theoretic Study。 --- p.8Chapter 1.4 --- Organization of Thesis --- p.9Chapter 2 --- Preliminaries --- p.13Chapter 2.1 --- MPEG Compression Scheme --- p.13Chapter 2.2 --- Problems of Transmitting MPEG Video --- p.17Chapter 2.3 --- Two-layer Coding and Transport Strategy --- p.19Chapter 2.3.1 --- Framework of MPEG-based Layering --- p.19Chapter 2.3.2 --- Transmission of GS and ES --- p.20Chapter 2.3.3 --- Problems of Two-layer Video Transmission --- p.20Chapter 3 --- Video Aggregation --- p.24Chapter 3.1 --- Motivation and Basic Concept of Video Aggregation --- p.25Chapter 3.1.1 --- Description of Video Aggregation --- p.28Chapter 3.2 --- MPEG Video Aggregation System --- p.29Chapter 3.2.1 --- Shortcomings of the MPEG Video Bundle Scenario with Two-Layer Coding and Cell-Level Multiplexing --- p.29Chapter 3.2.2 --- MPEG Video Aggregation --- p.31Chapter 3.2.3 --- MPEG Video Aggregation System Architecture --- p.33Chapter 3.3 --- Variations of MPEG Video Aggregation System --- p.35Chapter 3.4 --- Experimental Results --- p.38Chapter 3.4.1 --- Comparison of Video Aggregation and Cell-level Multi- plexing --- p.40Chapter 3.4.2 --- Varying Amount of the Allocated Bandwidth --- p.48Chapter 3.4.3 --- Varying Number of Sequences --- p.50Chapter 3.5 --- Conclusion --- p.53Chapter 3.6 --- Appendix: Alternative Implementation of MPEG Video Aggre- gation --- p.53Chapter 3.6.1 --- Profile Approach --- p.54Chapter 3.6.2 --- Bit-Plane Approach --- p.54Chapter 4 --- A Control-Theoretic Study of Video Traffic Adaptation --- p.58Chapter 4.1 --- Review of Previous Adaptation Schemes --- p.60Chapter 4.1.1 --- A Generic Model for Adaptation Scheme --- p.60Chapter 4.1.2 --- Objectives of Adaptation Controller --- p.61Chapter 4.2 --- Motivation for Control-Theoretic Study --- p.64Chapter 4.3 --- Linear Feedback Controller Model --- p.64Chapter 4.3.1 --- Encoder Model --- p.65Chapter 4.3.2 --- Adaptation Controller Model --- p.69Chapter 4.4 --- Analysis --- p.72Chapter 4.4.1 --- Stability --- p.73Chapter 4.4.2 --- Robustness against Coding-mode Switching --- p.83Chapter 4.4.3 --- Unit-Step Responses and Unit-Sample Responses --- p.84Chapter 4.5 --- Implementation --- p.91Chapter 4.6 --- Experimental Results --- p.95Chapter 4.6.1 --- Overall Performance of the Adaptation Scheme --- p.97Chapter 4.6.2 --- Weak-Control verus Strong-Control --- p.99Chapter 4.6.3 --- Varying Amount of Reserved Bandwidth --- p.101Chapter 4.7 --- Conclusion --- p.103Chapter 4.8 --- Appendix I: Further Research --- p.103Chapter 4.9 --- Appendix II: Review of Previous Adaptation Schemes --- p.106Chapter 4.9.1 --- Watanabe. et. al.'s Scheme --- p.106Chapter 4.9.2 --- MPEG's Scheme --- p.107Chapter 4.9.3 --- Lee et.al.'s Modification --- p.109Chapter 4.9.4 --- Chen's Adaptation Scheme --- p.110Chapter 5 --- Conclusion --- p.116Bibliography --- p.11

Transcoding of MPEG Bitstreams

This paper discusses the problem of transcoding as it may occur in, for instance, the following situation. Suppose a satellite transmits an MPEG-compressed video signal at say 9 Mbit/s. This signal must be relayed at a cable head end. However, since the cable capacity is only limited, the cable head end will want to relay this incoming signal at a lower bit-rate of, say, 5 Mbit/s. The problem is how to convert a compressed video signal of a given bit-rate into a compressed video signal of a lower bit-rate. The specific transcoding problem discussed in this paper is referred to as bit-rate conversion. Basically, a transcoder used for such a purpose will consist of a cascaded decoder and encoder. It is shown in the paper that the complexity of this combination can be significantly reduced. The paper also investigates the loss of picture quality that may be expected when a transcoder is in the transmission chain. The loss of quality as compared to that resulting in the case of transmission without a transcoder is studied by means of computations using simplified models of the transmission chains and by means of using computer simulations of the complete transmission chain. It will be shown that the presence of two quantizers, i.e. cascaded quantization, in the transmission chain is the main cause of extra losses, and it will be shown that the losses in terms of SNR will be some 0.5 ¿ 1.0 dB greater than in the case of a transmission chain without a transcoder

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Video surveillance systems are growing in size and complexity. Such systems typically consist of integrated modules of different vendors to cope with the increasing demands on network and storage capacity, intelligent video analytics, picture quality, and enhanced visual interfaces. Within a surveillance system, relevant information (like technical details on the video sequences, or analysis results of the monitored environment) is described using metadata standards. However, different modules typically use different standards, resulting in metadata interoperability problems. In this paper, we introduce the application of Semantic Web Technologies to overcome such problems. We present a semantic, layered metadata model and integrate it within a video surveillance system. Besides dealing with the metadata interoperability problem, the advantages of using Semantic Web Technologies and the inherent rule support are shown. A practical use case scenario is presented to illustrate the benefits of our novel approach

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