CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 智能化团队
Cheating Behavior Detection based-on Pictorial Structure Model
Lv Le1; Zhao Dongbin1; Fan Zhijiang2
Conference NameThe 2014 Chinese Control Conference
Conference Date28-30 July 2014
Conference PlaceNanjing, China
AbstractThe 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.
KeywordPose Estimation Cheating Behavior Detection Pictorial Structure Model Belief Propagation
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Document Type会议论文
Affiliation1.The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
2.USTECH(Beijing) Technology Co. Ltd.
Recommended Citation
GB/T 7714
Lv Le,Zhao Dongbin,Fan Zhijiang. Cheating Behavior Detection based-on Pictorial Structure Model[C],2014.
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