Mobile video surveillance represents a new paradigm that encompasses, on the one side, ubiquitous video acquisition and, on the other side, ubiquitous video processing and viewing, addressing both computer-based and human-based surveillance. There are many parameters that affect video quality but their combined effect is not well identified and Understood when video is transmitted over mobile/ wireless networks. In addition, video content has an impact on video quality under same network conditions. The main aim of this paper is the prediction of video quality combining the application and network level parameters for all content types. Firstly, video sequences are classified into groups Representing different content types using cluster analysis. The classification of contents is based on the temporal (movement) and spatial (edges, brightness) feature extraction. Second, to study and analyze the behavior of video quality for wide range variations of a set of selected parameters.

20101031.pdf

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