Detection of object security in crowed environment

This paper describes a new approach aimed at automatic identify events of abandoned and stolen objects detection in video surveillance system. Our method mainly include three steps of data processing: the first processing phrase is object extraction, involving a background subtraction algorithm which dynamically updates two sets of background. Then, extracted objects are classified as static or dynamic objects. Finally, a decision-making model is employed to calculate a confidence score for the classification about event, and an alarm will be automatically triggered if the score of corresponding action is higher than a pre-defined threshold. Also, Compared with the existing detection algorithm, the robustness and efficiency of the method was tested on our real time video surveillance system and evaluated by public database such as AVSS 2007 data sets.