relation: http://eprints.imtlucca.it/848/
title: Video anomaly detection in spatiotemporal context
creator: Jiang, Fan
creator: Yuanc, Junsong 
creator: Tsaftaris, Sotirios A.
creator: Katsaggelos, Aggelos K.
subject: TK Electrical engineering. Electronics Nuclear engineering
description: 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.
publisher: IEEE
date: 2010-09
type: Book Section
type: PeerReviewed
identifier:   Jiang, Fan and Yuanc, Junsong  and Tsaftaris, Sotirios A. and Katsaggelos, Aggelos K.  Video anomaly detection in spatiotemporal context.   In:  17th IEEE international conference on image processing (ICIP).   IEEE, 705 -708.  ISBN 978-1-4244-7992-4       (2010)  
relation: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5650993&isnumber=5648792
relation: 10.1109/ICIP.2010.5650993