Improved Human Gait Recognition - Archive ouverte HAL Accéder directement au contenu
Chapitre D'ouvrage Année : 2015

Improved Human Gait Recognition

Résumé

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.

Dates et versions

hal-03515437 , version 1 (19-01-2022)

Identifiants

Citer

Imad Rida, Ahmed Bouridane, Gian Luca Marcialis, Pierluigi Tuveri. Improved Human Gait Recognition. Image Analysis and Processing — ICIAP 2015, 9280, Springer International Publishing, pp.119-129, 2015, Lecture Notes in Computer Science, ⟨10.1007/978-3-319-23234-8_12⟩. ⟨hal-03515437⟩
15 Consultations
1 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More