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Fourth IEEE International Conference on Automatic Face and Gesture Recognition (FG'00)
Hand Gesture Recognition Using Input-Output Hidden Markov Models
Grenoble, France9
March 26-March 30
ISBN: 0-7695-0580-5
Sébastien Marcel, France Telecom CNET
Olivier Bernier, France Telecom CNET
Jean-Emmanuel Viallet, France Telecom CNET
Daniel Collobert, France Telecom CNET
A new hand gesture recognition method based on Input-Output Hidden Markov Models is presented. This method deals with the dynamic aspects of gestures. Gestures are extracted from a sequence of video images by tracking the skin-color blobs corresponding to the hand into a body-face space centered on the face of the user. Our goal is to recognize two classes of gestures: deictic and symbolic.
Index Terms:
Gesture recognition, Hidden Markov Models, Neural Networks
Citation:
Sébastien Marcel, Olivier Bernier, Jean-Emmanuel Viallet, Daniel Collobert, "Hand Gesture Recognition Using Input-Output Hidden Markov Models," fg, pp.456, Fourth IEEE International Conference on Automatic Face and Gesture Recognition (FG'00), 2000
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