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dc.contributor.advisorChristensen, Henrik
dc.contributor.authorSinghal, Prateek
dc.date.accessioned2016-05-27T13:12:37Z
dc.date.available2016-05-27T13:12:37Z
dc.date.created2016-05
dc.date.issued2016-05-03
dc.date.submittedMay 2016
dc.identifier.urihttp://hdl.handle.net/1853/54970
dc.description.abstractAn on-line 3D visual object tracking framework for monocular cameras by incorporating spatial knowledge and uncertainty from semantic mapping along with high frequency measurements from visual odometry is presented. Using a combination of vision and odometry that are tightly integrated we can increase the overall performance of object based tracking for semantic mapping. We present a framework for integration of the two data-sources into a coherent framework through uncertainty based fusion/arbitration.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherGeorgia Institute of Technology
dc.subjectSLAM
dc.subjectTracking
dc.subjectVision
dc.titleMultimodal tracking for robust pose estimation
dc.typeThesis
dc.description.degreeM.S.
dc.contributor.departmentComputer Science
thesis.degree.levelMasters
dc.contributor.committeeMemberHays, James
dc.contributor.committeeMemberBoots, Byron
dc.date.updated2016-05-27T13:12:37Z


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