TY - GEN
T1 - Video anomaly detection in spatiotemporal context
AU - Jiang, Fan
AU - Yuan, Junsong
AU - Tsaftaris, Sotirios A.
AU - Katsaggelos, Aggelos K.
PY - 2010
Y1 - 2010
N2 - Compared to other approaches that analyze object trajectories, we propose to detect anomalous video events at three levels considering spatiotemporal context of video objects, i.e., point anomaly, sequential anomaly, and co-occurrence anomaly. A hierarchical data mining approach is proposed to achieve this task. At each level, the frequency based analysis is performed to automatically discover regular rules of normal events. The events deviating from these rules are detected as anomalies. Experiments on real traffic video prove that the detected video anomalies are hazardous or illegal according to the traffic rule.
AB - Compared to other approaches that analyze object trajectories, we propose to detect anomalous video events at three levels considering spatiotemporal context of video objects, i.e., point anomaly, sequential anomaly, and co-occurrence anomaly. A hierarchical data mining approach is proposed to achieve this task. At each level, the frequency based analysis is performed to automatically discover regular rules of normal events. The events deviating from these rules are detected as anomalies. Experiments on real traffic video prove that the detected video anomalies are hazardous or illegal according to the traffic rule.
UR - http://www.scopus.com/inward/record.url?scp=78651069619&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78651069619&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2010.5650993
DO - 10.1109/ICIP.2010.5650993
M3 - Conference contribution
AN - SCOPUS:78651069619
SN - 9781424479948
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 705
EP - 708
BT - 2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
T2 - 2010 17th IEEE International Conference on Image Processing, ICIP 2010
Y2 - 26 September 2010 through 29 September 2010
ER -