Gait recognition under carrying condition: A static dynamic fusion method

Yu Guan, Chang Tsun Li, Yongjian Hu

Research output: Book chapter/Published conference paperConference paperpeer-review

Abstract

When an individual carries an object, such as a briefcase, conventional gait recognition algorithms based on average silhouette/Gait Energy Image (GEI) do not always perform well as the object carried may have the potential of being mistakenly regarded as a part of the human body. To solve such a problem, in this paper, instead of directly applying GEI to represent the gait information, we propose a novel dynamic feature template for classification. Based on this extracted dynamic information and some static feature templates (i.e., head part and trunk part), we cast gait recognition on the large USF (University of South Florida) database by adopting a static/dynamic fusion strategy. For the experiments involving carrying condition covariate, significant improvements are achieved when compared with other classic algorithms.
Original languageEnglish
Title of host publicationOptics, Photonics, and Digital Technologies for Multimedia Applications II
PublisherSPIE
Pages1-6
Number of pages6
Volume8436
ISBN (Print)9780819491282
DOIs
Publication statusPublished - 2012
EventOptics, Photonics, and Digital Technologies for Multimedia Applications II - Square Brussels Meeting Centre, Brussels, Belgium
Duration: 17 Apr 201218 Apr 2012
http://spie.org/EPE12/conferencedetails/optics-photonics-digital-technologies-multimedia-applications?SSO=1

Conference

ConferenceOptics, Photonics, and Digital Technologies for Multimedia Applications II
CountryBelgium
CityBrussels
Period17/04/1218/04/12
Internet address

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