Classifying and detecting group behaviour from visual surveillance data Hosie, Robin, Venkatesh, Svetha and West, Geoff 1998, Classifying and detecting group behaviour from visual surveillance data, in ICPR 1998 : Proceedings of the 14th International Conference on Pattern Recognition, IEEE, Los Alamitos, Calif., pp. 602-604, doi: 10.1109/ICPR.1998.711215. Attached Files Name Description MIMEType Size Downloads venkatesh-classifyingand-1998.pdf Published version application/pdf 180.36KB 30 Title Classifying and detecting group behaviour from visual surveillance data Author(s) Hosie, Robin Venkatesh, Svetha orcid.org/0000-0001-8675-6631 West, Geoff Conference name International Conference on Pattern Recognition (14th : 1998 : Brisbane, Qld.) Conference location Brisbane, Qld. Conference dates 16-20 Aug. 1998 Title of proceedings ICPR 1998 : Proceedings of the 14th International Conference on Pattern Recognition Editor(s) Jain, Anil K. Venkatesh, Svetha Lovell, Brian Carrington Publication date 1998 Conference series International Conference on Pattern Recognition Start page 602 End page 604 Total pages 3 Publisher IEEE Place of publication Los Alamitos, Calif. Keyword(s) group behaviour detection image segmentation learning systems pair primitives pairwise movement patterns pattern classification target tracking temporal sequence visual surveillance system Summary We outline an approach to classifying and detecting behaviours from surveillance data. Simple pairwise movement patterns are learned and used as building blocks to describe behaviour over a temporal sequence, or compared with other pairs to detect group behaviour. As the pair primitives are easy to redefine and learn, and complex behaviour over time is specified by the user as a sequence of pair primitives, this approach provides a flexible yet robust method of detecting complex movement in a wide variety of domains. Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. ISBN 0818685131 9780818685132 Language eng DOI 10.1109/ICPR.1998.711215 Field of Research 089999 Information and Computing Sciences not elsewhere classified Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences HERDC Research category E1.1 Full written paper - refereed Copyright notice ©1998, IEEE Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30044890 Document type: Conference Paper Collections: School of Information Technology Open Access Collection Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Tue, 01 May 2012, 11:04:41 EST Wed, 09 May 2012, 12:59:49 EST Wed, 09 May 2012, 13:02:14 EST Tue, 24 Jun 2014, 08:53:06 EST Wed, 06 Aug 2014, 16:01:26 EST Mon, 15 Sep 2014, 15:43:58 EST Tue, 06 Sep 2016, 18:53:12 EST Tue, 05 Dec 2017, 12:32:10 EST Fri, 07 Sep 2018, 15:56:09 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 364 Abstract Views, 30 File Downloads  -  Detailed Statistics Created: Tue, 01 May 2012, 11:04:41 EST

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