Neural Network classifiers for automated video surveillance

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dc.contributor.author Jan, T
dc.contributor.author Piccardi, M
dc.contributor.author Hintz, TB
dc.contributor.editor Hulle, M
dc.contributor.editor Larsen, J
dc.date.accessioned 2009-11-09T05:39:14Z
dc.date.issued 2003-01
dc.identifier.citation Proceedings of 2003 IEEE International workshop on neural networks for signal processing, 2003, pp. 729 - 739
dc.identifier.isbn 0-7803-8178-5
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/3167
dc.description.abstract n automated visual surveillance applications, detection of suspicious human behaviors is of great practical importance. However due to random nature of human movements, reliable classification of suspicious human movements can be very difficult. Artificial neural network (ANN) classifiers can perform well however their computational requirements can be very large for real time implementation. In this paper, a data-based modeling neural network such as modified probabilistic neural network (MPNN) is introduced which partitions the decision space nonlinearly in order to achieve reliable classification, however still with acceptable computations. The experiment shows that the compact MPNN attains good classification performance compared to that of other larger conventional neural network based classifiers such as multilayer perceptron (MLP) and self organising map (SOM).
dc.publisher IEEE Press
dc.title Neural Network classifiers for automated video surveillance
dc.type Conference Proceeding
dc.parent Proceedings of 2003 IEEE International workshop on neural networks for signal processing
dc.journal.number en_US
dc.publocation New York, USA en_US
dc.identifier.startpage 729 en_US
dc.identifier.endpage 739 en_US
dc.cauo.name FEIT.School of Computing and Communications en_US
dc.conference Verified OK en_US
dc.conference IEEE International Workshop on Neural Networks for Signal Processing
dc.conference.location Toulouse, France en_US
dc.for 080104 Computer Vision
dc.for 080109 Pattern Recognition and Data Mining
dc.personcode 830145
dc.personcode 020073
dc.personcode 020524
dc.percentage 50 en_US
dc.classification.name Pattern Recognition and Data Mining en_US
dc.classification.type FOR-08 en_US
dc.custom IEEE International Workshop on Neural Networks for Signal Processing en_US
dc.date.activity 20030917 en_US
dc.date.activity 2003-09-17
dc.location.activity Toulouse, France en_US
dc.description.keywords image classification multilayer perceptrons self-organising feature maps surveillance en_US
dc.description.keywords image classification multilayer perceptrons self-organising feature maps surveillance
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computing and Communications
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Systems, Management and Leadership
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10
utslib.collection.history Closed (ID: 3)


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