This paper describes an approach aimed at automatic identification of events of abandoned and stolen objects in variety
environment. Our approach mainly include three steps of data processing: the first processing phrase is object extraction,
involving a dual-time background subtraction algorithm which dynamically updates two sets of background. Then,
extracted objects are classified as static or dynamic objects and human or non-human 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 certainty of action is higher than a pre-defined threshold. Also, 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
datasets.
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