Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/10982
DC FieldValueLanguage
dc.contributorDepartment of Electronic and Information Engineering-
dc.creatorKim, MH-
dc.creatorChau, LP-
dc.creatorSiu, WC-
dc.date.accessioned2014-12-19T04:13:42Z-
dc.date.available2014-12-19T04:13:42Z-
dc.identifier.urihttp://hdl.handle.net/10397/10982-
dc.description2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012, Seoul, 20-23 May 2012en_US
dc.language.isoenen_US
dc.titleKeyframe selection for motion capture using motion activity analysisen_US
dc.typeConference Paperen_US
dc.identifier.spage612-
dc.identifier.epage615-
dc.identifier.doi10.1109/ISCAS.2012.6272106-
dcterms.abstractMotion capture data acquired from high definition cameras creates accurate human motion representation but introduces many redundant frames which pose a problem in data storage and motion retrieval purposes. In this paper, a keyframing approach is proposed to reduce the motion data by extracting keyframes using motion analysis approach in sampling windows. Motion changes in sampling windows for original motion without frame skipping and with frame skipping are computed. The difference in the motion changes is the main aspect in deciding whether the frames in sampling windows are possible candidates for keyframe selection. Simulation results showed that the proposed method is able to achieve an overall good visual quality for different types of motion. It also gives an improvement of up to 52% in terms of mean square error measurement, as compared to the existing keyframe extraction method, which is curve simplification method.-
dcterms.bibliographicCitationISCAS 2012 - 2012 IEEE International Symposium on Circuits and Systems, 2012, 6272106, p. 612-615-
dcterms.issued2012-
dc.identifier.scopus2-s2.0-84866611361-
dc.identifier.rosgroupidr57190-
dc.description.ros2011-2012 > Academic research: refereed > Refereed conference paper-
Appears in Collections:Conference Paper
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