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dc.contributor.advisorStavdahl, Øyvindnb_NO
dc.contributor.authorFernandez Cuesta, Roaldnb_NO
dc.date.accessioned2014-12-19T14:03:23Z
dc.date.available2014-12-19T14:03:23Z
dc.date.created2011-02-01nb_NO
dc.date.issued2010nb_NO
dc.identifier393818nb_NO
dc.identifierntnudaim:5417nb_NO
dc.identifier.urihttp://hdl.handle.net/11250/260268
dc.description.abstractThis thesis presents a method for performing tracking and estimation of head position and orientation by means of template based particle filtering. The implementation is designed to withstand high levels of occlusion and noise, and allow for system dynamics to be accounted for. To accelerate the computation, GPGPU techniques are used to enable the GPU to function a co-processor, resulting in real-time performance. A method is devised for dynamic creation of feature points used in the particle filter. Furthermore, the graphics pipeline is used to overlay and visualize the tracking, as well as play a key role in the dynamic template functionality. Finally, a benchmarking system is suggested and developed for carrying out controlled evaluation of tracking methods in general.nb_NO
dc.languageengnb_NO
dc.publisherInstitutt for teknisk kybernetikknb_NO
dc.subjectntnudaim:5417no_NO
dc.subjectSIE3 teknisk kybernetikkno_NO
dc.subjectTilpassede datasystemerno_NO
dc.titleMotion Analysis: Model Based Head Pose Estimation of Infantsnb_NO
dc.typeMaster thesisnb_NO
dc.source.pagenumber131nb_NO
dc.contributor.departmentNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for teknisk kybernetikknb_NO


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