Tracking of dynamic hand gestures on a mobile platform

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dc.contributor.author Prior, Robert
dc.date.accessioned 2017-09-08T19:54:30Z
dc.date.available 2017-09-08T19:54:30Z
dc.date.copyright 2017 en_US
dc.date.issued 2017-09-08
dc.identifier.uri https://dspace.library.uvic.ca//handle/1828/8554
dc.description.abstract Hand 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.language English eng
dc.language.iso en en_US
dc.rights Available to the World Wide Web en_US
dc.subject Computer Vision en_US
dc.subject mobile en_US
dc.subject GPU en_US
dc.subject hand gesture en_US
dc.title Tracking of dynamic hand gestures on a mobile platform en_US
dc.type Thesis en_US
dc.contributor.supervisor Capson, David W.
dc.degree.department Department of Electrical and Computer Engineering en_US
dc.degree.level Master of Applied Science M.A.Sc. en_US
dc.description.scholarlevel Graduate en_US

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