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Proceedings Paper

Adaptive gesture recognition combining HMM models and geometrical features
Author(s): Pu Cheng; Jie Zhou
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Paper Abstract

Hand gesture recognition is receiving more and more attentions due to its potential use in many applications. In this paper, we propose a novel gesture spotting and recognition method, which combines the information of hand motion parameter, the matching result of HMM models and the recognition result based on geometrical features of hand trajectory to spot and recognize the gesture. Besides, we also study the method of adjusting classifiers to make the gesture recognition system adapt to specific users. Experimental results have proved the effectiveness of the proposed method.

Paper Details

Date Published: 2 December 2011
PDF: 6 pages
Proc. SPIE 8004, MIPPR 2011: Pattern Recognition and Computer Vision, 80040J (2 December 2011); doi: 10.1117/12.901204
Show Author Affiliations
Pu Cheng, Tsinghua Univ. (China)
Jie Zhou, Tsinghua Univ. (China)


Published in SPIE Proceedings Vol. 8004:
MIPPR 2011: Pattern Recognition and Computer Vision
Jonathan Roberts; Jie Ma, Editor(s)

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