Hand shape estimation under complex backgrounds for sign language recognition

Authors:
Yasushi Hamada;Nobutaka Shimada;Yoshiaki Shirai
Affiliations:
Dept. of Computer, Controlled Mechanical Systems, Osaka University, Osaka, Japan;Dept. of Computer, Controlled Mechanical Systems, Osaka University, Osaka, Japan;Dept. of Computer, Controlled Mechanical Systems, Osaka University, Osaka, Japan
Venue:
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Year:
2004

Citing 3
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Abstract

This paper presents a method of hand shape estimation under complex backgrounds which may include a face. We reduce matching candidate models by using a shape transition network. When the hand moves fast, a hand image is blurred and the hand contour is not available. In such a case, no candidate matches to the input image. By adding models having only the position and velocity of the hand, matched models are correctly traced in the transition network. For each matching candidate, the best-matched position is determined. For selecting the best matched model, conventional methods assumed that prominent edges are extracted only from true hand contour. However, the prominent edges may often extracted on the background and may not extracted some parts on the hand contour. We propose a matching criterion defined as the length of the part of the contour covering the true hand contour by considering edge existence probability in the background. We show experimental results to support the effectiveness of the proposed criterion.