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1. Prior, Robert. Tracking of dynamic hand gestures on a mobile platform.

Degree: Department of Electrical and Computer Engineering, 2017, University of Victoria

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. Advisors/Committee Members: Capson, David W. (supervisor).

Subjects/Keywords: Computer Vision; mobile; GPU; hand gesture

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APA (6th Edition):

Prior, R. (2017). Tracking of dynamic hand gestures on a mobile platform. (Masters Thesis). University of Victoria. Retrieved from https://dspace.library.uvic.ca//handle/1828/8554

Chicago Manual of Style (16th Edition):

Prior, Robert. “Tracking of dynamic hand gestures on a mobile platform.” 2017. Masters Thesis, University of Victoria. Accessed November 19, 2017. https://dspace.library.uvic.ca//handle/1828/8554.

MLA Handbook (7th Edition):

Prior, Robert. “Tracking of dynamic hand gestures on a mobile platform.” 2017. Web. 19 Nov 2017.

Vancouver:

Prior R. Tracking of dynamic hand gestures on a mobile platform. [Internet] [Masters thesis]. University of Victoria; 2017. [cited 2017 Nov 19]. Available from: https://dspace.library.uvic.ca//handle/1828/8554.

Council of Science Editors:

Prior R. Tracking of dynamic hand gestures on a mobile platform. [Masters Thesis]. University of Victoria; 2017. Available from: https://dspace.library.uvic.ca//handle/1828/8554

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