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Proceedings Paper

Context based gait recognition
Author(s): Shermin Bazazian; Marina Gavrilova
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Paper Abstract

Gait recognition has recently become a popular topic in the field of biometrics. However, the main hurdle is the insufficient recognition rate in the presence of low quality samples. The main focus of this paper is to investigate how the performance of a gait recognition system can be improved using additional information about behavioral patterns of users and the context in which samples have been taken. The obtained results show combining the context information with biometric data improves the performance of the system at a very low cost. The amount of improvement depends on the distinctiveness of the behavioral patterns and the quality of the gait samples. Using the appropriate distinctive behavioral models it is possible to achieve a 100% recognition rate.

Paper Details

Date Published: 10 May 2012
PDF: 6 pages
Proc. SPIE 8407, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012, 84070J (10 May 2012); doi: 10.1117/12.921449
Show Author Affiliations
Shermin Bazazian, Univ. of Calgary (Canada)
Marina Gavrilova, Univ. of Calgary (Canada)


Published in SPIE Proceedings Vol. 8407:
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012
Jerome J. Braun, Editor(s)

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