Please use this identifier to cite or link to this item: https://doi.org/10.1007/s00138-011-0371-7
DC FieldValue
dc.title3-D-2-D spatiotemporal registration for sports motion analysis
dc.contributor.authorLeow, W.K.
dc.contributor.authorWang, R.
dc.contributor.authorLeong, H.W.
dc.date.accessioned2013-07-04T07:45:33Z
dc.date.available2013-07-04T07:45:33Z
dc.date.issued2012
dc.identifier.citationLeow, W.K., Wang, R., Leong, H.W. (2012). 3-D-2-D spatiotemporal registration for sports motion analysis. Machine Vision and Applications 23 (6) : 1177-1194. ScholarBank@NUS Repository. https://doi.org/10.1007/s00138-011-0371-7
dc.identifier.issn09328092
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/39612
dc.description.abstractComputer systems are increasingly being used for sports training. Existing sports training systems either require expensive 3-D motion capture systems or do not provide intelligent analysis of user's sports motion. This paper presents a framework for affordable and intelligent sports training systems for general users. The user is assumed to perform the same type of sport motion as an expert, and therefore the performer's motion is more or less similar to the expert's reference motion. The performer's motion is recorded by a single stationary camera, and the expert's 3-D reference motion is captured only once by a commercial motion capture system. Under such assumptions, sports motion analysis is formulated as a 3-D-2-D spatiotemporal motion registration problem. A novel algorithm is developed to perform spa-tiotemporal registration of the expert's 3-D reference motion and a performer's 2-D input video, thereby computing the deviation of the performer's motion from the expert's motion. The algorithm can effectively handle ambiguous situations in a single video such as depth ambiguity of body parts and partial occlusion. Test results on Taichi and golf swing motion show that, despite using only single video, the algorithm can compute 3-D posture errors that reflect the performer's actual motion error. © Springer-Verlag 2012.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/s00138-011-0371-7
dc.sourceScopus
dc.subjectBelief propagation
dc.subjectDynamic programming
dc.subjectHuman motion analysis
dc.subjectSpatiotemporal registration
dc.typeArticle
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1007/s00138-011-0371-7
dc.description.sourcetitleMachine Vision and Applications
dc.description.volume23
dc.description.issue6
dc.description.page1177-1194
dc.description.codenMVAPE
dc.identifier.isiut000309875400008
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