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A novel statistical framework for modeling the intrinsic structure of crowded scenes and detecting abnormal activities is presented in this paper. The proposed framework essentially turns the anomaly detection process into two parts, namely, motion pattern representation and crowded context modeling. During the first stage, we averagely divide the spatiotemporal volume into atomic blocks. Considering the fact that mutual interference of several human body parts potentially happen in the samedoi:10.1109/icpr.2014.383 dblp:conf/icpr/LuWMST14 fatcat:hxhlijvm6fhyfo5des3qoceaka