Description: 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.
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