Hand gesture recognition based on segmented singular value decomposition

Authors:
Jing Liu;Manolya Kavakli
Affiliations:
Department of Computing, Macquarie University, Australia;Department of Computing, Macquarie University, Australia
Venue:
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II
Year:
2010

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Abstract

The increasing interest in gesture recognition is inspired largely by creating a system which can identify specific human gestures and using gestures to convey information or control devices. In this paper we present a novel approach for recognizing hand gestures. The proposed approach is based on segmented singular value decomposition(SegSV D) and considers both local and global information regarding gesture data. In this approach, first singular vectors and singular values are evaluated together to define the similarity of two gestures. Experiments with hand gesture data prove that our approach can recognize gestures with high accuracy.