Active Contours: The Application of Techniques from Graphics,Vision,Control Theory and Statistics to Visual Tracking of Shapes in Motion
Device Independence and Extensibility in Gesture Recognition
VR '03 Proceedings of the IEEE Virtual Reality 2003
An Introduction to the Kalman Filter
An Introduction to the Kalman Filter
Gesture-recognition with Non-referenced Tracking
3DUI '06 Proceedings of the 3D User Interfaces
Camera phone based motion sensing: interaction techniques, applications and performance study
UIST '06 Proceedings of the 19th annual ACM symposium on User interface software and technology
iGesture: A General Gesture Recognition Framework
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
International Journal of Bioinformatics Research and Applications
GART: the gesture and activity recognition toolkit
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments
A trajectory-based approach for device independent gesture recognition in multimodal user interfaces
HAID'10 Proceedings of the 5th international conference on Haptic and audio interaction design
A trajectory-based approach for device independent gesture recognition in multimodal user interfaces
HAID'10 Proceedings of the 5th international conference on Haptic and audio interaction design
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With the rise of technology in all areas of life new interaction techniques are required. With gestures and voice being the most natural ways to interact, it is a goal to also support this in human-computer interaction. In this paper, we introduce our approach to multimodal interaction in smart home environments and illustrate how device independent gesture recognition can be of great support in this area. We describe a trajectory-based approach that is applied to support device independent dynamic hand gesture recognition from vision systems, accelerometers or pen devices. The recorded data from the different devices is transformed to a common basis (2D-space) and the feature extraction and recognition is done on this basis. In a comprehensive case study we show the feasibility of the recognition and the integration with a multimodal and adaptive home operating system.