Individual Identification Using Gait Sequences under Different Covariate Factors

  • Yogarajah Pratheepan
  • Joan V. Condell
  • Girijesh Prasad
Conference paper

DOI: 10.1007/978-3-642-04667-4_9

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5815)
Cite this paper as:
Pratheepan Y., Condell J.V., Prasad G. (2009) Individual Identification Using Gait Sequences under Different Covariate Factors. In: Fritz M., Schiele B., Piater J.H. (eds) Computer Vision Systems. ICVS 2009. Lecture Notes in Computer Science, vol 5815. Springer, Berlin, Heidelberg

Abstract

Recently, gait recognition for individual identification has received increased attention from biometrics researchers as gait can be captured at a distance using low-resolution capturing device. Human gait properties can be affected by different clothing and carrying objects (i.e. covariate factors). Most of the literature shows that these covariate factors give difficulties for individual identification based on gait. In this paper, we propose a novel method that generates dynamic and static feature templates of the sequences of silhouette images (Dynamic Static Silhouette Templates (DSSTs)) to overcome this issue. Here the DSST is calculated from Motion History Images (MHIs). The experimental results show that our method overcomes issues arising from differing clothing and the carrying of objects.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Yogarajah Pratheepan
    • 1
  • Joan V. Condell
    • 1
  • Girijesh Prasad
    • 1
  1. 1.School of Computing and Intelligent SystemsUniversity of UlsterUK

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