Probabilistic video-based gesture recognition using self-organizing feature maps

Authors:
George Caridakis;Christos Pateritsas;Athanasios Drosopoulos;Andreas Stafylopatis;Stefanos Kollias
Affiliations:
School of Electrical and Computer Engineering, National Technical University of Athens, Greece;School of Electrical and Computer Engineering, National Technical University of Athens, Greece;School of Electrical and Computer Engineering, National Technical University of Athens, Greece;School of Electrical and Computer Engineering, National Technical University of Athens, Greece;School of Electrical and Computer Engineering, National Technical University of Athens, Greece
Venue:
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Year:
2007

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Abstract

Present work introduces a probabilistic recognition scheme for hand gestures. Self organizing feature maps are used to model spatiotemporal information extracted through image processing. Two models are built for each gesture category and, along with appropriate distance metrics, produce a validated classification mechanism that performs consistently during experi-ments on acted gestures video sequences.