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.