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dc.contributor.authorBulbul, A.en_US
dc.contributor.authorArpa, S.en_US
dc.contributor.authorCapin, T.en_US
dc.date.accessioned2016-02-08T10:59:44Z
dc.date.available2016-02-08T10:59:44Z
dc.date.issued2014en_US
dc.identifier.issn0097-8493
dc.identifier.urihttp://hdl.handle.net/11693/26436
dc.description.abstractWe present a model to determine the perceptually significant elements in animated 3D scenes using a motion-saliency method. Our model clusters vertices with similar motion-related behaviors. To find these similarities, for each frame of an animated mesh sequence, vertices' motion properties are analyzed and clustered using a Gestalt approach. Each cluster is analyzed as a single unit and representative vertices of each cluster are used to extract the motion-saliency values of each group. We evaluate our method by performing an eye-tracker-based user study in which we analyze observers' reactions to vertices with high and low saliencies. The experiment results verify that our proposed model correctly detects the regions of interest in each frame of an animated mesh. © 2014 Elsevier Ltd.en_US
dc.language.isoEnglishen_US
dc.source.titleComputers and Graphics (Pergamon)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.cag.2014.04.003en_US
dc.subjectAnimated meshesen_US
dc.subjectComputer graphicsen_US
dc.subjectSaliencyen_US
dc.subjectVisual perceptionen_US
dc.subjectHuman computer interactionen_US
dc.subject3D scenesen_US
dc.subjectAnimated meshesen_US
dc.subjectRegions of interesten_US
dc.subjectSaliencyen_US
dc.subjectUser studyen_US
dc.subjectVisual perceptionen_US
dc.subjectComputer graphicsen_US
dc.titleA clustering-based method to estimate saliency in 3D animated meshesen_US
dc.typeArticleen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.citation.spage11en_US
dc.citation.epage20en_US
dc.citation.volumeNumber43en_US
dc.citation.issueNumber1en_US
dc.identifier.doi10.1016/j.cag.2014.04.003en_US
dc.publisherElsevier Ltden_US


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