An immunological approach to raising alarms in video surveillance Sasmita, Lukman, Liu, Wanquan and Venkatesh, Svetha 2005, An immunological approach to raising alarms in video surveillance, GESTS international transactions on computer science and engineering, vol. 2, pp. 191-199. Attached Files Name Description MIMEType Size Downloads Title An immunological approach to raising alarms in video surveillance Author(s) Sasmita, Lukman Liu, Wanquan Venkatesh, Svetha orcid.org/0000-0001-8675-6631 Journal name GESTS international transactions on computer science and engineering Volume number 2 Start page 191 End page 199 Total pages 9 Publisher Global Engineering, Science, and Technology Society Publication date 2005 ISSN 1738-6438 Summary Inspired by the human immune system, and in particular the negative selection algorithm, we propose a learning mechanism that enables the detection of abnormal activities. Three detectors for detecting abnormal activity are generated using negative selection. Tracks gathered by people’s movements in a room are used for experimentation and results have shown that the classifier is able to discriminate abnormal from normal activities in terms of both trajectory and time spent at a location. Language eng Field of Research 080104 Computer Vision Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture) HERDC Research category C2.1 Other contribution to refereed journal Persistent URL http://hdl.handle.net/10536/DRO/DU:30044305 Document type: Journal Article Collection: School of Information Technology   Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Thu, 05 Apr 2012, 16:05:01 EST Wed, 18 Apr 2012, 16:21:54 EST Wed, 18 Apr 2012, 16:22:44 EST Wed, 18 Apr 2012, 16:24:34 EST Tue, 24 Apr 2012, 14:28:27 EST Mon, 30 Apr 2012, 10:01:38 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 50 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Thu, 05 Apr 2012, 16:05:01 EST

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