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A Hierarchical Bayesian Network for Real-Time Continuous Hand Gesture Recognition  

Huh, Sung-Ju (고려대학교 컴퓨터.통신공학부)
Lee, Seong-Whan (고려대학교 컴퓨터.통신공학부)
Publication Information
Journal of KIISE:Software and Applications / v.36, no.12, 2009 , pp. 1028-1033 More about this Journal
Abstract
This paper presents a real-time hand gesture recognition approach for controlling a computer. We define hand gestures as continuous hand postures and their movements for easy expression of various gestures and propose a Two-layered Bayesian Network (TBN) to recognize those gestures. The proposed method can compensate an incorrectly recognized hand posture and its location via the preceding and following information. In order to vertify the usefulness of the proposed method, we implemented a Virtual Mouse interface, the gesture-based interface of a physical mouse device. In experiments, the proposed method showed a recognition rate of 94.8% and 88.1% for a simple and cluttered background, respectively. This outperforms the previous HMM-based method, which had results of 92.4% and 83.3%, respectively, under the same conditions.
Keywords
Hierarchical Bayesian Network; Hand Gesture Recognition; Human-Computer Interface;
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