Tracking of dynamic hand gestures on a mobile platform

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dc.contributor.authorPrior, Robert
dc.contributor.supervisorCapson, David W.
dc.date.accessioned2017-09-08T19:54:30Z
dc.date.available2017-09-08T19:54:30Z
dc.date.copyright2017en_US
dc.date.issued2017-09-08
dc.degree.departmentDepartment of Electrical and Computer Engineeringen_US
dc.degree.levelMaster of Applied Science M.A.Sc.en_US
dc.description.abstractHand gesture recognition is an expansive and evolving field. Previous work addresses methods for tracking hand gestures primarily with specialty gaming/desktop environments in real time. The method proposed here focuses on enhancing performance for mobile GPU platforms with restricted resources by limiting memory use/transfers and by reducing the need for code branches. An encoding scheme has been designed to allow contour processing typically used for finding fingertips to occur efficiently on a GPU for non-touch, remote manipulation of on-screen images. Results show high resolution video frames can be processed in real time on a modern mobile consumer device, allowing for fine grained hand movements to be detected and tracked.en_US
dc.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/8554
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.subjectComputer Visionen_US
dc.subjectmobileen_US
dc.subjectGPUen_US
dc.subjecthand gestureen_US
dc.titleTracking of dynamic hand gestures on a mobile platformen_US
dc.typeThesisen_US

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