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dc.contributor.authorHalit, C.en_US
dc.contributor.authorCapin, T.en_US
dc.date.accessioned2016-02-08T09:55:04Z
dc.date.available2016-02-08T09:55:04Z
dc.date.issued2011en_US
dc.identifier.issn1546-4261
dc.identifier.urihttp://hdl.handle.net/11693/22071
dc.description.abstractMotion capture is an increasingly popular animation technique; however data acquired by motion capture can become substantial. This makes it difficult to use motion capture data in a number of applications, such as motion editing, motion understanding, automatic motion summarization, motion thumbnail generation, or motion database search and retrieval. To overcome this limitation, we propose an automatic approach to extract keyframes from a motion capture sequence. We treat the input sequence as motion curves, and obtain the most salient parts of these curves using a new proposed metric, called 'motion saliency'. We select the curves to be analysed by a dimension reduction technique, Principal Component Analysis (PCA). We then apply frame reduction techniques to extract the most important frames as keyframes of the motion. With this approach, around 8% of the frames are selected to be keyframes for motion capture sequences. © 2011 John Wiley & Sons, Ltd.en_US
dc.language.isoEnglishen_US
dc.source.titleComputer Animation and Virtual Worldsen_US
dc.relation.isversionofhttp://dx.doi.org/10.1002/cav.380en_US
dc.subjectKeyframe extractionen_US
dc.subjectMotion captureen_US
dc.subjectMotion saliencyen_US
dc.subjectPCAen_US
dc.subjectAnimation techniquesen_US
dc.subjectMultiscalesen_US
dc.titleMultiscale motion saliency for keyframe extraction from motion capture sequencesen_US
dc.typeArticleen_US
dc.departmentDepartment of Computer Engineering
dc.citation.spage3en_US
dc.citation.epage14en_US
dc.citation.volumeNumber22en_US
dc.citation.issueNumber1en_US
dc.identifier.doi10.1002/cav.380en_US
dc.publisherJohn Wiley & Sons Ltd.en_US


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