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Individual Identification Using Gait Sequences under Different Covariate Factors

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Yogarajah, Pratheepan, Condell, JV and Prasad, G (2009) Individual Identification Using Gait Sequences under Different Covariate Factors. In: 7th International Conference on Computer Vision Systems (ICVS), 2009, Liege, Belgium. Springer Berlin / Heidelberg. Vol 5815/2009 10 pp. [Conference contribution]

Full text not available from this repository.

URL: http://www.springerlink.com/content/f4w2054387206132/

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

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.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:12220
Deposited By:Professor Girijesh Prasad
Deposited On:09 Mar 2010 11:59
Last Modified:22 Jul 2011 15:41

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