Real-Time Fingertip Tracking and Gesture Recognition
IEEE Computer Graphics and Applications
Vision-Based Gesture Recognition: A Review
GW '99 Proceedings of the International Gesture Workshop on Gesture-Based Communication in Human-Computer Interaction
From a Typology of Gestures to a Procedure for Gesture Production
GW '01 Revised Papers from the International Gesture Workshop on Gesture and Sign Languages in Human-Computer Interaction
Multi-finger and whole hand gestural interaction techniques for multi-user tabletop displays
Proceedings of the 16th annual ACM symposium on User interface software and technology
Interacting with large displays from a distance with vision-tracked multi-finger gestural input
Proceedings of the 18th annual ACM symposium on User interface software and technology
User-defined gestures for surface computing
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
WUW - wear Ur world: a wearable gestural interface
CHI '09 Extended Abstracts on Human Factors in Computing Systems
User-defined gestures for connecting mobile phones, public displays, and tabletops
Proceedings of the 12th international conference on Human computer interaction with mobile devices and services
Gestures for large display control
GW'09 Proceedings of the 8th international conference on Gesture in Embodied Communication and Human-Computer Interaction
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We report a series of empirical studies investigating gesture as an interaction technique in pervasive computing. In our first study, participants generated gestures for given tasks and from these we identified archetypal common gestures. Furthermore, we discovered that many of these usergenerated gestures were performed in 3D. We implemented a computer vision based 3D gesture recognition system and applied it in a further study in which participants used the common gestures generated in the first study. We investigated the trade off between system performance and human performance and preferences, deriving design recommendations. We achieved 84% recognition accuracy by our prototype 3D gesture recognition system after tuning it through the use of simple heuristics. The most popular gestures from Study 1 were regarded by participants in Study 2 as best matching the task they represented, and they produced the fewest recall errors.