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

Authors: Farid Parvini, Cyrus Shahabi

Addresses: 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

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.

Keywords: multi-stream human sensor data; sensor data analysis; gesture recognition; static gestures; dynamic gestures; user-independent; device-independent; range of motion; American Sign Language; ASL; bioinformatics; mechanics; biomechanics; biomedical data; biomedical engineering.

DOI: 10.1504/IJBRA.2007.011832

International Journal of Bioinformatics Research and Applications, 2007 Vol.3 No.1, pp.4 - 23

Published online: 26 Dec 2006 *

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