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Many works have been proposed on detecting individual anomalies in crowd scenes, i.e., human behaviors anomalous with respect to the rest of the behaviors. In this paper, we introduce a new concept of contextual anomaly into the field of crowd analysis, i.e., the behaviors themselves are normal but they are anomalous in a specific context. Our system follows an unsupervised approach. It automatically discovers important contextual information from the crowd video and detects the blobsdoi:10.1109/icip.2009.5414535 dblp:conf/icip/JiangWK09 fatcat:kxippeptz5cq7gp5l4lbpw4hqm