| Title: | GART: The Gesture and Activity Recognition Toolkit |
| Author: | Brashear, Helene ; Kim, Jung Soo ; Lyons, Kent ; Starner, Thad ; Westeyn, Tracy |
| 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 |
| Date: | 2007-07 |
| Contributor: |
Georgia Institute of Technology. College of Computing
Georgia Institute of Technology. Graphics, Visualization and Usability Center |
| Publisher: | Georgia Institute of Technology |
| Subject: |
Gesture recognition
User interface toolkit |
| Files | Size | Format | View |
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| gartpaper.pdf | 223.3Kb |
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