Detection of Abnormal Behaviour in a Surveillance Environment Using Control Charts

Hommes, Stefan; State, Radu; Zinnen, Andreas; Engel, Thomas

Reference : Detection of Abnormal Behaviour in a Surveillance Environment Using Control Charts


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/9534

Title :	Detection of Abnormal Behaviour in a Surveillance Environment Using Control Charts
Language :	English
Author, co-author :	Hommes, Stefan [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	State, Radu [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC)]
	Zinnen, Andreas [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Engel, Thomas [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Publication date :	2011
Main document title :	8th IEEE International Conference on Advanced Video and Signal-Based Surveillance, 2011
Pages :	113-118
Peer reviewed :	Yes
ISBN :	978-1-4577-0845-9
Event name :	IEEE International Conference on Advanced Video and Signal based Surveillance (AVSS)
Event date :	From 30-08-2011 to 02-09-2011
Event place (city) :	Klagenfurt
Event country :	Austria
Abstract :	[en] This paper introduces a new approach to unsupervised detection of abnormal sequences of images in video surveillance data. We leverage an online object detection method and statistical process control techniques in order to identify suspicious sequences of events. Our method assumes a training phase in which the spatial distribution of objects is learned, followed by a chart-based tracking process. We evaluate the performance of our method on a standard dataset and have implemented a publicly available opensource prototype.
Permalink :	http://hdl.handle.net/10993/9534
Commentary :	8th IEEE International Conference on Advanced Video and Signal based Surveillance (AVSS)

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