Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/69449
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dc.titleArticulated object registration using simulated physical force/moment for 3D human motion tracking
dc.contributor.authorNi, B.
dc.contributor.authorWinkler, S.
dc.contributor.authorKassim, A.
dc.date.accessioned2014-06-19T03:00:49Z
dc.date.available2014-06-19T03:00:49Z
dc.date.issued2007
dc.identifier.citationNi, B.,Winkler, S.,Kassim, A. (2007). Articulated object registration using simulated physical force/moment for 3D human motion tracking. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 4814 LNCS : 212-224. ScholarBank@NUS Repository.
dc.identifier.isbn9783540757023
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/69449
dc.description.abstractIn this paper, we present a 3D registration algorithm based on simulated physical force/moment for articulated human motion tracking. Provided with sparsely reconstructed 3D human surface points from multiple synchronized cameras, the tracking problem is equivalent to fitting the 3D model to the scene points. The simulated physical force/ moment generated by the displacement between the model and the scene points is used to align the model with the scene points in an Iterative Closest Points (ICP) [1] approach. We further introduce a hierarchical scheme for model state updating, which automatically incorporates human kinematic constraints. Experimental results on both synthetic and real data from several unconstrained motion sequences demonstrate the efficiency and robustness of our proposed method. © Springer-Verlag Berlin Heidelberg 2007.
dc.sourceScopus
dc.subject3D registration
dc.subjectArticulated human motion tracking
dc.subjectIterative closest points
dc.subjectKinematic constraints
dc.subjectSimulated physical force/moment
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume4814 LNCS
dc.description.page212-224
dc.identifier.isiutNOT_IN_WOS
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