Cheating behavior detection based-on pictorial structure model
Le Lv, Dongbin Zhao, Zhijiang Fan · 2014
The video surveillance system is widely used in various areas. However, it is an intractable problem to process a large number of video data manually. There are many intelligent systems developed to analyze human behavior and detect unusual events, however, few concerns the cheating behavior in examinations. In this paper, we use video surveillance system to detect cheating behavior in the examination. The pose estimation method is presented to detect the cheating behavior, based on the analysis of the implementation environment. More in detail, the pictorial structure is adopted to model the human body and a required pose and skin color information is utilized to build the human appearance model. Finally, the belief propagation algorithm is used to infer the maximum a posterior pose. The experiment shows the effectiveness of our method.