Articulated Pose Identification with Sparse Point Features

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dc.contributor.author Li, Bo
dc.contributor.author Meng, Qinggang
dc.contributor.author Holstein, Horst
dc.date.accessioned 2008-12-17T10:10:47Z
dc.date.available 2008-12-17T10:10:47Z
dc.date.issued 2004-06-01
dc.identifier.citation Li , B , Meng , Q & Holstein , H 2004 , ' Articulated Pose Identification with Sparse Point Features ' IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics , vol 34 , no. 3 , pp. 1412-1422 . en
dc.identifier.issn 1083-4419
dc.identifier.other PURE: 97077
dc.identifier.other dspace: 2160/1738
dc.identifier.uri http://hdl.handle.net/2160/1738
dc.description Holstein, Horst, Li, B., Meng, Q., (2004) 'Articulated Pose Identification with Sparse Point Features', IEEE Transactions on Systems, Man and Cybernetics, Part B 34(3) pp.1412-1422 RAE2008 en
dc.description.abstract We propose a general algorithm for identifying an arbitrary pose of an articulated subject with sparse point features. The algorithm aims to identify a one-to-one correspondence between a model point-set and an observed point-set taken from freeform motion of the articulated subject. We avoid common assumptions such as pose similarity or small motions with respect to the model, and assume no prior knowledge from which to infer an initial or partial correspondence between the two point-sets. The algorithm integrates local segment-based correspondences under a set of affine transformations, and a global hierarchical search strategy. Experimental results, based on synthetic pose and real-world human motion data demonstrate the ability of the algorithm to perform the identification task. Reliability is increasingly compromised with increasing data noise and segmental distortion, but the algorithm can tolerate moderate levels. This work contributes to establishing a crucial self-initializing identification in model-based point-feature tracking for articulated motion. en
dc.format.extent 11 en
dc.language.iso eng
dc.relation.ispartof IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics en
dc.title Articulated Pose Identification with Sparse Point Features en
dc.type Text en
dc.type.publicationtype Article (Journal) en
dc.identifier.doi http://dx.doi.org/10.1109/TSMCB.2004.825914
dc.contributor.institution Intelligent Robotics Group en
dc.contributor.institution Institute of Mathematics & Physics (ADT) en
dc.contributor.institution Department of Computer Science en
dc.description.status Peer reviewed en


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