2 December 2011 Adaptive gesture recognition combining HMM models and geometrical features
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Proceedings Volume 8004, MIPPR 2011: Pattern Recognition and Computer Vision; 80040J (2011) https://doi.org/10.1117/12.901204
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China
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.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Pu Cheng, Pu Cheng, Jie Zhou, Jie Zhou, } "Adaptive gesture recognition combining HMM models and geometrical features", Proc. SPIE 8004, MIPPR 2011: Pattern Recognition and Computer Vision, 80040J (2 December 2011); doi: 10.1117/12.901204; https://doi.org/10.1117/12.901204
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