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. / Graduate
| Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/8554 |
| Date | 08 September 2017 |
| Creators | Prior, Robert |
| Contributors | Capson, David W. |
| Source Sets | University of Victoria |
| Language | English, English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
| Rights | Available to the World Wide Web |
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