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Please use this identifier to cite or link to this item:
http://hdl.handle.net/1853/27819
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| Title: | GART: The Gesture and Activity Recognition Toolkit |
| Authors: | Brashear, Helene
Kim, Jung Soo
Lyons, Kent
Starner, Thad
Westeyn, Tracy
Georgia Institute of Technology. College of Computing
Georgia Institute of Technology. Graphics, Visualization and Usability Center |
| Subjects : | Gesture recognition
User interface toolkit |
| Issue Date: | Jul-2007 |
| Publisher: | Georgia Institute of Technology |
| Abstract: | The Gesture and Activity Recognition Toolit (GART) is
a user interface toolkit designed to enable the development of gesture-based
applications. GART provides an abstraction to machine learning
algorithms suitable for modeling and recognizing different types of
gestures. The toolkit also provides support for the data collection and
the training process. In this paper, we present GART and its machine
learning abstractions. Furthermore, we detail the components of the
toolkit and present two example gesture recognition applications. |
| Description: | Presented at the 12th International Conference on Human-Computer Interaction, Beijing, China, July 2007.
The original publication is available at www.springerlink.com |
| Type: | Proceedings |
| URI: | http://hdl.handle.net/1853/27819 |
| Appears in Collections: | Contextual Computing Group Publications
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