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

A robust speed-invariant gait recognition system for walker and runner identification

Tools
- Tools
+ Tools

Guan, Yu and Li, Chang-Tsun (2013) A robust speed-invariant gait recognition system for walker and runner identification. In: 2013 International Conference on Biometrics (ICB), Madrid, Spain, 4-7 Jun 2013. Published in: Proceedings : 2013 International Conference on Biometrics (ICB) pp. 1-8. doi:10.1109/ICB.2013.6612965

[img]
Preview
PDF
ICB_Guan %282%29_Guan___.pdf - Accepted Version - Requires a PDF viewer.

Download (871Kb) | Preview
Official URL: http://dx.doi.org/10.1109/ICB.2013.6612965

Request Changes to record.

Abstract

In real-world scenarios, walking/running speed is one of the most common covariate factors that can affect the performance of gait recognition systems. By assuming the effect caused by the speed changes (from the query walkers/runners) are intra-class variations that the training data (i.e., gallery) fails to capture, overfitting to the less representative training data may be the main problem that degrades the performance. In this work, we employ a general model based on random subspace method to solve this problem. More specifically, for query gaits in unknown speeds, we try to reduce the generalization errors by combining a large number of weak classifiers. We evaluate our method on two benchmark databases, i.e., Infrared CASIA-C dataset and Treadmill OU-ISIR-A dataset. For the cross-speed walking/running gait recognition experiments, nearly perfect results are achieved, significantly higher than other state-of-the-art algorithms. We also study the unknown-speed runner identification solely using the walking gait gallery, and the encouraging experimental results suggest the effectiveness of our method in such cross-mode gait recognition tasks.

Item Type: Conference Item (Paper)
Subjects: Q Science > QA Mathematics
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Science, Engineering and Medicine > Science > Computer Science
Library of Congress Subject Headings (LCSH): Gait in humans -- Mathematical models, Computer vision
Journal or Publication Title: Proceedings : 2013 International Conference on Biometrics (ICB)
Publisher: IEEE
Book Title: 2013 International Conference on Biometrics (ICB)
Official Date: 2013
Dates:
DateEvent
2013Published
Page Range: pp. 1-8
DOI: 10.1109/ICB.2013.6612965
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 28 December 2015
Date of first compliant Open Access: 28 December 2015
Conference Paper Type: Paper
Title of Event: 2013 International Conference on Biometrics (ICB)
Type of Event: Conference
Location of Event: Madrid, Spain
Date(s) of Event: 4-7 Jun 2013

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics

twitter

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