A review of vision-based gait recognition methods for human identification Wang, Jin, She, Mary, Nahavandi, Saeid and Kouzani, Abbas 2010, A review of vision-based gait recognition methods for human identification, in DICTA 2010 : Proceedings of the Digital Image Computing : Techniques and Application, IEEE, Piscataway, N.J., pp. 320-327. Attached Files Name Description MIMEType Size Downloads she-areviewof-2010.pdf Published version application/pdf 568.68KB 4332 Title A review of vision-based gait recognition methods for human identification Author(s) Wang, Jin She, Mary orcid.org/0000-0001-8191-0820 Nahavandi, Saeid orcid.org/0000-0002-0360-5270 Kouzani, Abbas orcid.org/0000-0002-6292-1214 Conference name Digital Image Computing : Techniques and Application Conference (2010 : Sydney, N.S.W.) Conference location Sydney, N.S.W. Conference dates 1-3 Dec. 2010 Title of proceedings DICTA 2010 : Proceedings of the Digital Image Computing : Techniques and Application Editor(s) Zhang, Jian Shen, Chunhua Geers, Glenn Wu, Qiang Publication date 2010 Conference series Australian Pattern Recognition Society Conference Start page 320 End page 327 Total pages 8 Publisher IEEE Place of publication Piscataway, N.J. Summary Human identification by gait has created a great deal of interest in computer vision community due to its advantage of inconspicuous recognition at a relatively far distance. This paper provides a comprehensive survey of recent developments on gait recognition approaches. The survey emphasizes on three major issues involved in a general gait recognition system, namely gait image representation, feature dimensionality reduction and gait classification. Also, a review of the available public gait datasets is presented. The concluding discussions outline a number of research challenges and provide promising future directions for the field. 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 0769542719 9780769542713 Language eng Field of Research 080104 Computer Vision Socio Economic Objective 810105 Intelligence HERDC Research category E1 Full written paper - refereed HERDC collection year 2010 Copyright notice ©2010, IEEE Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30034514 Document type: Conference Paper Collections: Centre for Material and Fibre Innovation Open Access Collection GTP Research 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 Mon, 09 May 2011, 12:45:37 EST Mon, 09 May 2011, 12:49:23 EST Tue, 10 May 2011, 09:39:24 EST Tue, 24 May 2011, 10:06:49 EST Tue, 24 May 2011, 10:08:01 EST Tue, 24 May 2011, 10:09:24 EST Tue, 24 May 2011, 10:20:36 EST Tue, 24 May 2011, 10:22:29 EST Tue, 24 May 2011, 10:23:25 EST Tue, 24 May 2011, 10:24:16 EST Tue, 24 May 2011, 10:25:30 EST Tue, 24 May 2011, 10:26:46 EST Fri, 16 Mar 2012, 18:53:43 EST Tue, 15 Jul 2014, 15:51:09 EST Wed, 27 Aug 2014, 22:37:34 EST Wed, 21 Oct 2015, 14:00:22 EST Tue, 06 Sep 2016, 17:01:02 EST Tue, 05 Dec 2017, 10:49:40 EST Fri, 07 Sep 2018, 15:24:46 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 128 times in Scopus Search Google Scholar Access Statistics: 983 Abstract Views, 4340 File Downloads  -  Detailed Statistics Created: Mon, 09 May 2011, 12:45:22 EST by Sandra Dunoon

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