An algorithmic approach for static and dynamic gesture recognition utilising mechanical and biomechanical characteristics

Authors:
Farid Parvini;Cyrus Shahabi
Affiliations:
Computer Science Department, University of Southern California, 941 W. 37th Place, Los Angeles, CA 90089-0781, USA.;Computer Science Department, University of Southern California, 941 W. 37th Place, Los Angeles, CA 90089-0781, USA
Venue:
International Journal of Bioinformatics Research and Applications
Year:
2007

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Abstract

We propose a novel approach for recognising static and dynamic hand gestures by analysing the raw data streams generated by the sensors attached to the human hands. We utilise the concept of 'range of motion' in the movement of fingers and exploit this characteristic to analyse the acquired data for recognising hand signs. Our approach for hand gesture recognition addresses two major problems: user-dependency and device-dependency. Furthermore, we show that our approach neither requires calibration nor involves training. We apply our approach for recognising American Sign Language (ASL) signs and show that more than 75% accuracy in sign recognition can be achieved.