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dc.contributor.authorBauer, Martin
dc.contributor.authorEslitzbichler, Markus
dc.contributor.authorGrasmair, Markus
dc.date.accessioned2018-03-19T12:45:35Z
dc.date.available2018-03-19T12:45:35Z
dc.date.created2017-10-17T15:45:35Z
dc.date.issued2017
dc.identifier.citationInverse Problems and Imaging. 2017, 11 (4), 601-621.nb_NO
dc.identifier.issn1930-8337
dc.identifier.urihttp://hdl.handle.net/11250/2491044
dc.description.abstractMotions of virtual characters in movies or video games are typically generated by recording actors using motion capturing methods. Animations generated this way often need postprocessing, such as improving the periodicity of cyclic animations or generating entirely new motions by interpolation of existing ones. Furthermore, search and classification of recorded motions becomes more and more important as the amount of recorded motion data grows. In this paper, we will apply methods from shape analysis to the processing of animations. More precisely, we will use the by now classical elastic metric model used in shape matching, and extend it by incorporating additional inexact feature point information, which leads to an improved temporal alignment of different animations.nb_NO
dc.language.isoengnb_NO
dc.publisherAmerican Institute of Mathematical Sciences (AIMS)nb_NO
dc.titleLandmark-guided elastic shape analysis of human character motionsnb_NO
dc.typeJournal articlenb_NO
dc.description.versionsubmittedVersionnb_NO
dc.source.pagenumber601-621nb_NO
dc.source.volume11nb_NO
dc.source.journalInverse Problems and Imagingnb_NO
dc.source.issue4nb_NO
dc.identifier.doi10.3934/ipi.2017028
dc.identifier.cristin1505310
dc.description.localcode© 2017. This is the authors' manuscript to the article. The final authenticated version is available online at: http://www.aimsciences.org/journals/displayArticlesnew.jsp?paperID=14300nb_NO
cristin.unitcode194,63,15,0
cristin.unitnameInstitutt for matematiske fag
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.qualitycode1


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