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.
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Lyons, K., Brashear, H., Westeyn, T., Kim, J.S., Starner, T. (2007). GART: The Gesture and Activity Recognition Toolkit. In: Jacko, J.A. (eds) Human-Computer Interaction. HCI Intelligent Multimodal Interaction Environments. HCI 2007. Lecture Notes in Computer Science, vol 4552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73110-8_78
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DOI: https://doi.org/10.1007/978-3-540-73110-8_78
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