Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

Random subspace method for gait recognition

Tools
- Tools
+ Tools

Guan, Yu, Li, Chang-Tsun and Hu, Yongjian (2012) Random subspace method for gait recognition. In: IEEE International Conference on Multimedia and Expo Workshops (ICMEW), Melbourne, Australia, 9-13 Jul 2012 . Published in: Proceedings of the 2012 international conference on multimedia and expo workshops pp. 284-289. ISBN 9780769547299. doi:10.1109/ICMEW.2012.55

Research output not available from this repository.

Request-a-Copy directly from author or use local Library Get it For Me service.

Official URL: http://dx.doi.org/10.1109/ICMEW.2012.55

Request Changes to record.

Abstract

Overfitting is a common problem for gait recognition algorithms when gait sequences in gallery for training are acquired under a single walking condition. In this paper, we propose an approach based on the random subspace method (RSM) to address such overlearning problems. Initially, two-dimensional Principle Component Analysis (2DPCA) is adopted to obtain the full hypothesis space (i.e., eigenspace). Multiple inductive biases (i.e., subspaces) are constructed, each with the corresponding basis vectors randomly chosen from the initial eigenspace. This procedure can not only largely avoid overadaptation but also facilitate dimension reduction. The final classification is achieved by the decision committee which follows a majority voting criterion from the labeling results of all the subspaces. Experimental results on the benchmark USF HumanID gait database show that the proposed method is a feasible framework for gait recognition under unknown walking conditions.

Item Type: Conference Item (Paper)
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions: Faculty of Science, Engineering and Medicine > Science > Computer Science
Library of Congress Subject Headings (LCSH): Biometric identification, Gait in humans -- Measurement
Journal or Publication Title: Proceedings of the 2012 international conference on multimedia and expo workshops
Publisher: IEEE
ISBN: 9780769547299
Book Title: 2012 IEEE International Conference on Multimedia and Expo Workshops
Official Date: 2012
Dates:
DateEvent
2012Published
Page Range: pp. 284-289
DOI: 10.1109/ICMEW.2012.55
Status: Peer Reviewed
Publication Status: Published
Conference Paper Type: Paper
Title of Event: IEEE International Conference on Multimedia and Expo Workshops (ICMEW)
Type of Event: Conference
Location of Event: Melbourne, Australia
Date(s) of Event: 9-13 Jul 2012

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item
twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us