Pairwise Shape configuration-based PSA for gait recognition under small viewing angle change

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dc.contributor.author Kusakunniran, Worapan en_US
dc.contributor.author Wu, Qiang en_US
dc.contributor.author Zhang, Jian en_US
dc.contributor.author Li, Hongdong en_US
dc.contributor.editor Gian Luca Foresti; Bernhard Rinner en_US
dc.date.accessioned 2012-10-12T03:36:18Z
dc.date.available 2012-10-12T03:36:18Z
dc.date.issued 2011 en_US
dc.identifier 2011002112 en_US
dc.identifier.citation Kusakunniran Worapan et al. 2011, 'Pairwise Shape configuration-based PSA for gait recognition under small viewing angle change', , IEEE, USA, , pp. 17-22. en_US
dc.identifier.issn 978-1-4577-0845-9 en_US
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/19156
dc.description.abstract Two main components of Procrustes Shape Analysis (PSA) are adopted and adapted specifically to address gait recognition under small viewing angle change: 1) Procrustes Mean Shape (PMS) for gait signature description; 2) Procrustes Distance (PD) for similarity measurement. Pairwise Shape Configuration (PSC) is proposed as a shape descriptor in place of existing Centroid Shape Configuration (CSC) in conventional PSA. PSC can better tolerate shape change caused by viewing angle change than CSC. Small variation of viewing angle makes large impact only on global gait appearance. Without major impact on local spatio-temporal motion, PSC which effectively embeds local shape information can generate robust view-invariant gait feature. To enhance gait recognition performance, a novel boundary re-sampling process is proposed. It provides only necessary re-sampled points to PSC description. In the meantime, it efficiently solves problems of boundary point correspondence, boundary normalization and boundary smoothness. This re-sampling process adopts prior knowledge of body pose structure. Comprehensive experiment is carried out on the CASIA gait database. The proposed method is shown to significantly improve performance of gait recognition under small viewing angle change without additional requirements of supervised learning, known viewing angle and multi-camera system, when compared with other methods in literatures. en_US
dc.language English en_US
dc.publisher IEEE en_US
dc.relation.isbasedon en_US
dc.title Pairwise Shape configuration-based PSA for gait recognition under small viewing angle change en_US
dc.parent 2011 8th IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS) en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation USA en_US
dc.identifier.startpage 17 en_US
dc.identifier.endpage 22 en_US
dc.cauo.name FEIT.School of Computing and Communications en_US
dc.conference Verified OK en_US
dc.for 080104 en_US
dc.personcode 117151 en_US
dc.personcode 000748 en_US
dc.personcode 109852 en_US
dc.personcode 0000059310 en_US
dc.percentage 40 en_US
dc.classification.name Computer Vision en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom The 8th IEEE International Conference Advanced Video and Signal-Based Surveillance en_US
dc.date.activity 20110830 en_US
dc.location.activity Klagenfurt, Austria en_US
dc.description.keywords procrustes mean shape gait signature description centroid shape configuration en_US


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