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

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dc.contributor.author Kusakunniran, W
dc.contributor.author Wu, Q
dc.contributor.author Zhang, J
dc.contributor.author Li, H
dc.date.accessioned 2012-10-12T03:36:18Z
dc.date.issued 2011
dc.identifier.citation 2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2011, 2011, pp. 17 - 22
dc.identifier.isbn 9781457708459
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. © 2011 IEEE.
dc.relation.isbasedon 10.1109/AVSS.2011.6027286
dc.subject procrustes mean shape gait signature description centroid shape configuration
dc.subject procrustes mean shape gait signature description centroid shape configuration
dc.title Pairwise shape configuration-based PSA for gait recognition under small viewing angle change
dc.type Conference Proceeding
dc.parent 2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2011
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 080109 Pattern Recognition and Data Mining
dc.for 080106 Image Processing
dc.for 080104 Computer Vision
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
dc.description.keywords Advanced characterization
dc.description.keywords Analytical tool
dc.description.keywords Organic matter
dc.description.keywords Water
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computing and Communications


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