A New Approach for Real-Time Detection of Abandoned and Stolen Objects

In this paper a new approach aimed at automatic identify events of abandoned and stolen objects detection in video surveillance system is described. Our method mainly includes 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, the robustness and efficiency of the method is tested on our real-time video surveillance system and evaluated by public database such as AVSS 2007 datasets.