Vision-Based recognition of hand shapes in taiwanese sign language

Authors:
Jung-Ning Huang;Pi-Fuei Hsieh;Chung-Hsien Wu
Affiliations:
Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan;Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan;Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan
Venue:
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
Year:
2005

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Abstract

The pixel-based shape representation has been sensitive to rotation. In this paper, we propose a pixel-based descriptor that is invariant with rotation and scale for the hand shape recognition in Taiwanese Sign Language (TSL). Based on the property that a hand shape is characteristic of a unique pointing direction, angle normalization is used to meet the rotation-invariant requirement. With angle normalization, the traces of class covariance matrices have been reduced almost all over the classes of hand shapes, implying a less overlap between classes. It is confirmed by the experiments that show an increase in recognition accuracy.