Improved human gait recognition

Rida, Imad, Bouridane, Ahmed, Marcialis, Gian Luca and Tuveri, Pierluigi (2015) Improved human gait recognition. In: Image Analysis and Processing. Lecture Notes in Computer Science, 9280 . Springer, London, pp. 119-129. ISBN 978-3-319-23233-1

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Official URL: http://dx.doi.org/10.1007/978-3-319-23234-8_12

Abstract

Gait recognition is an emerging biometric technology which aims to identify people purely through the analysis of the way they walk. The technology has attracted interest as a method of identification because of its non-invasiveness, since it does not require the subject’s cooperation. However, "covariates" which include clothing, carrying conditions, and other intra-class variations affect the recognition performances. This paper proposes a feature selection mask which is able to select most relevant discriminative features for human recognition to alleviate the impact of covariates so as to improve the recognition performances. The proposed method has been evaluated using CASIA Gait Database (Dataset B) and the experimental results demonstrate that the proposed technique yields 77.38 % of correct recognition

Item Type: Book Section
Additional Information: Biometrics, feature selection, gait, model free
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Nicola King
Date Deposited: 03 Nov 2015 15:17
Last Modified: 10 Nov 2016 12:40
URI: http://nrl.northumbria.ac.uk/id/eprint/24288

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