Hand Tension as a Gesture Segmentation Cue
Hand gesture segmentation is a difficult problem that must be overcome if gestural interfaces are to be practical. This paper sets out a recognition-led approach that focuses on the actual recognition techniques required for gestural interaction. Within this approach, a holistic view of the gesture input data stream is taken that considers what links the low-level and high-level features of gestural communication. Using this view, a theory is proposed that a state of high hand tension can be used as a gesture segmentation cue for certain classes of gestures. A model of hand tension is developed and then applied successfully to segment two British Sign Language sentence fragments.
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