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dc.contributor.advisorÇapın, Tolga
dc.contributor.authorDirican, Hüseyin
dc.date.accessioned2016-01-08T18:27:26Z
dc.date.available2016-01-08T18:27:26Z
dc.date.issued2014
dc.identifier.urihttp://hdl.handle.net/11693/15960
dc.descriptionAnkara : The Department of Computer Engineering and the Graduate School of Engineering and Science of Bilkent University, 2014.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2014.en_US
dc.descriptionIncludes bibliographical references leaves 53-56.en_US
dc.description.abstractRealistic human motions is an essential part of diverse range of media, such as feature films, video games and virtual environments. Motion capture provides realistic human motion data using sensor technology. However, motion capture data is not flexible. This drawback limits the utility of motion capture in practice. In this thesis, we propose a two-stage approach that makes the motion captured data reusable to synthesize new motions in real-time via motion graphs. Starting from a dataset of various motions, we construct a motion graph of similar motion segments and calculate the parameters, such as blending parameters, needed in the second stage. In the second stage, we synthesize a new human motion in realtime, depending on the blending techniques selected. Three different blending techniques, namely linear blending, cubic blending and anticipation-based blending, are provided to the user. In addition, motion clip preference approach, which is applied to the motion search algorithm, enable users to control the motion clip types in the result motion.en_US
dc.description.statementofresponsibilityDirican, Hüseyinen_US
dc.format.extentxii, 58 leaves, charts, illustrationsen_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectComputer animationen_US
dc.subjectHuman motion synthesisen_US
dc.subjectMotion captureen_US
dc.subjectMotion graphsen_US
dc.subjectBlendingen_US
dc.subject.lccT385 .D575 2014en_US
dc.subject.lcshComputer graphics.en_US
dc.subject.lcshComputer animation.en_US
dc.titleData-driven synthesis of realistic human motion using motion graphsen_US
dc.typeThesisen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.publisherBilkent Universityen_US
dc.description.degreeM.S.en_US
dc.identifier.itemidB147594


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