eprintid: 848
rev_number: 18
eprint_status: archive
userid: 35
dir: disk0/00/00/08/48
datestamp: 2011-09-08 13:25:13
lastmod: 2013-03-05 15:33:33
status_changed: 2011-09-08 13:25:13
type: book_section
metadata_visibility: show
item_issues_count: 0
creators_name: Jiang, Fan
creators_name: Yuanc, Junsong 
creators_name: Tsaftaris, Sotirios A.
creators_name: Katsaggelos, Aggelos K.
creators_id: 
creators_id: 
creators_id: sotirios.tsaftaris@imtlucca.it
creators_id: 
title: Video anomaly detection in spatiotemporal context
ispublished: pub
subjects: TK
divisions: CSA
full_text_status: none
keywords: anomalous video events; co-occurrence anomaly; frequency based analysis; hierarchical data mining approach; object trajectory; real traffic video anomaly detection; sequential anomaly; spatiotemporal context; video object; data mining; spatiotemporal phenomena; traffic; video surveillance
abstract: 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.
date: 2010-09
date_type: published
publisher: IEEE
pagerange: 705 -708
event_title: Image Processing (ICIP), 2010 17th IEEE International Conference on
id_number: 10.1109/ICIP.2010.5650993
refereed: TRUE
isbn: 978-1-4244-7992-4 
book_title: 17th IEEE international conference on image processing (ICIP)
official_url: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5650993&isnumber=5648792
citation:   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)