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ICPR
2008
IEEE

Robust modeling and recognition of hand gestures with dynamic Bayesian network

13 years 10 months ago
Robust modeling and recognition of hand gestures with dynamic Bayesian network
In this paper, we propose a new gesture recognition model for a set of both one-hand and two-hand gestures based on the dynamic Bayesian network framework which makes it easy to represent the relationship among features and incorporate new information to the model. Unlike the coupled HMM, the proposed model has room for common hidden variables which are believed to be shared between two variables. In an experiment with ten isolated gestures, we obtained a recognition rate upwards of 99.59% with leave-one-out cross validation. The proposed model is believed to have a strong potential for successful applications to other related problems such as sign languages.
Heung-Il Suk, Bong-Kee Sin, Seong-Whan Lee
Added 30 May 2010
Updated 30 May 2010
Type Conference
Year 2008
Where ICPR
Authors Heung-Il Suk, Bong-Kee Sin, Seong-Whan Lee
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