Human-machine interfaces play a role of growing importance as computer technology continues to evolve. Motivated by the desire to provide users with an intuitive gesture input system, we describe the design of a recursive filter applied to the vision-based gesture interpretation problem. The gestures are modeled as a hidden Markov model with the state representing the gesture sequences, and the observations being the current static hand pose. At each time step the recursive filter updates its estimate of what gesture is occurring based on the current extracted pose information. The result is a robust system which provides the user with continual feedback during compound gestures.<>
Recursive identification of gesture inputs using hidden Markov models
01.01.1994
610456 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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