3D Human Posture Segmentation By Spectral Clustering With Surface Normal Constraint

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dc.contributor.author Cheng, Joseph en_US
dc.contributor.author Qiao, Mu en_US
dc.contributor.author Bian, Wei en_US
dc.contributor.author Tao, Dacheng en_US
dc.contributor.editor en_US
dc.date.accessioned 2012-02-02T10:03:54Z
dc.date.available 2012-02-02T10:03:54Z
dc.date.issued 2011 en_US
dc.identifier 2010004626 en_US
dc.identifier.citation Cheng Joseph et al. 2011, '3D Human Posture Segmentation By Spectral Clustering With Surface Normal Constraint', Elsevier Science Bv, vol. 91, no. 9, pp. 2204-2212. en_US
dc.identifier.issn 0165-1684 en_US
dc.identifier.other C1 en_US
dc.identifier.uri http://hdl.handle.net/10453/15188
dc.description.abstract In this paper, we propose a new algorithm for partitioning human posture represented by 3D point clouds sampled from the surface of human body. The algorithm is formed as a constrained extension of the recently developed segmentation method, spectral clu en_US
dc.language en_US
dc.publisher Elsevier Science Bv en_US
dc.relation.hasversion Accepted manuscript version
dc.relation.isbasedon http://dx.doi.org/10.1016/j.sigpro.2011.04.003 en_US
dc.title 3D Human Posture Segmentation By Spectral Clustering With Surface Normal Constraint en_US
dc.parent Signal Processing en_US
dc.journal.volume 91 en_US
dc.journal.number 9 en_US
dc.publocation Amsterdam en_US
dc.identifier.startpage 2204 en_US
dc.identifier.endpage 2212 en_US
dc.cauo.name FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.for 080100 en_US
dc.personcode 0000051486 en_US
dc.personcode 0000062912 en_US
dc.personcode 115849 en_US
dc.personcode 111502 en_US
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity WOS:000291772700005 en_US
dc.description.keywords NA en_US
dc.staffid 111502 en_US


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