Gait recognition based on modified phase-only correlation

Rida, Imad, Al-Maadeed, Somaya and Bouridane, Ahmed (2016) Gait recognition based on modified phase-only correlation. Signal, Image and Video Processing, 10 (3). pp. 463-470. ISSN 1863-1703

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Official URL: http://dx.doi.org/10.1007/s11760-015-0766-4

Abstract

Gait recognition is an emerging biometric technology aiming to identify people purely through the analysis of the way they walk. The technology has attracted interest as a method of identification because it is noncontact and does not require the subject’s cooperation. Clothing, carrying conditions and other intra-class variations, also referred to as “covariates,” affect the performance of gait recognition systems. This paper proposes a supervised feature extraction method, which is able to select relevant discriminative features for human recognition to mitigate the impact of covariates and hence improve the recognition performances. The proposed method is evaluated using the CASIA gait database (dataset B), and the experimental results suggest that our method yields 81.40 % of correct classification when compared against similar techniques which do not exceed 77.96 %.

Item Type: Article
Uncontrolled Keywords: Gait recognition, phase-only correlation, feature selection, biometric recognition
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer Science and Digital Technologies
Depositing User: Becky Skoyles
Date Deposited: 07 Apr 2015 10:13
Last Modified: 02 Mar 2016 11:30
URI: http://nrl.northumbria.ac.uk/id/eprint/21961

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