Gait recognition based on modified phase-only correlation. Issue 3 (March 2016)

• Record Type: Journal Article
• Authors: Rida, Imad; Almaadeed, Somaya; Bouridane, Ahmed
• Is Part Of: Signal, image and video processing. Volume 10:Issue 3(2016)
• Page Start: 463
• Page End: 470
• Publication Date: 2016-03
• Subjects: Gait recognition -- Phase-only correlation -- Feature selection -- Biometric recognition; Signal processing -- Digital techniques -- Periodicals; Image processing -- Digital techniques -- Periodicals; Digital video -- Periodicals; 621.3822
• DOI: 10.1007/s11760-015-0766-4
• Languages: English
• ISSNs: 1863-1703

Abstract

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 %.