Video Based Crowd Density Estimation and Prediction System for a Wide Area Surveillance

Visual surveillance in dynamic scenes, especially for human and some objects is one of the most active research areas. An attempt has been made to this issue in this work. It has wide spectrum of promising application including human identification to detect the suspicious behavior, crowd flux statistics, and congestion analysis using multiple cameras. In this paper deals with the problem of detecting and tracking multiple moving people in a static background. Detection of foreground object is done by background subtraction. Detected objects are identified and analyzed through different blobs. Then tracking is performed by matching corresponding features of blob. An algorithm has been developed in this perspective using Angular Deviation of Center of Gravity (ADCG), which gives a satisfying result for segmentation of human object.

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