An Approach to Glove-Based Gesture Recognition
Proceedings of the 13th International Conference on Human-Computer Interaction. Part II: Novel Interaction Methods and Techniques
Fuzzy clustering of human motor motion
Applied Soft Computing
Hand gesture recognition based on segmented singular value decomposition
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II
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
Convexity local contour sequences for gesture recognition
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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Gesture recognition techniques often suffer from beinghighly device-dependent and hard to extend. If a system istrained using data from a specific glove input device, thatsystem is typically unusable with any other input device.The set of gestures that a system is trained to recognize istypically not extensible, without retraining the entire system.We propose a novel gesture recognition frameworkto address these problems. This framework is based on amulti-layered view of gesture recognition. Only the lowestlayer is device dependent; it converts raw sensor valuesproduced by the glove to a glove-independent semanticdescription of the hand. The higher layers of our frame-workcan be reused across gloves, and are easily extensibleto include new gestures. We have experimentally evaluatedour framework and found that it yields comparable performanceto conventional techniques, while substantiating ourclaims of device independence and extensibility.