You are not logged in.
Openly accessible

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 3173

Title A review of vision-based gait recognition methods for human identification
Author(s) Wang, Jin
She, MaryORCID iD for She, Mary orcid.org/0000-0001-8191-0820
Nahavandi, SaeidORCID iD for Nahavandi, Saeid orcid.org/0000-0002-0360-5270
Kouzani, AbbasORCID iD for 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
Connect to link resolver
 
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
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 87 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 677 Abstract Views, 3181 File Downloads  -  Detailed Statistics
Created: Mon, 09 May 2011, 12:45:22 EST by Sandra Dunoon

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.