Presentation 2007-10-26
Hand Gesture Recognition Based on Dynamic Bayesian Network Framework(Internationa Session 5)
Heung-Il Suk, Bong-Kee Sin, Beom-Joon Cho,
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Abstract(in English) It is natural to use hand gestures in interacting with computers because hand gestures are freer in movements and much more expressive than any other body parts. In this paper, we define and recognize ten hand gestures including two-hand gestures as well as one-hand gestures. Skin blobs in a frame are segmented by two different skin color models combined and each skin blob is modeled with a Gaussian distribution. The motion of hands is defined by the changes of the mean of each Gaussian and the relative position between two hands, each hand and a face. A new gesture recognition model is proposed based on the dynamic Bayesian network framework which is relatively easy to represent the relationship among features and to incorporate new features or information into a model. Experimental results showed high recognition rate up to 99.59% with our small dataset in isolated gesture recognition.
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Keyword(in English) Dynamic Bayesian network / Hidden Markov model / Hand gesture recognition
Paper # PRMU2007-112
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Conference Information
Committee PRMU
Conference Date 2007/10/18(1days)
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Registration To Pattern Recognition and Media Understanding (PRMU)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Hand Gesture Recognition Based on Dynamic Bayesian Network Framework(Internationa Session 5)
Sub Title (in English)
Keyword(1) Dynamic Bayesian network
Keyword(2) Hidden Markov model
Keyword(3) Hand gesture recognition
1st Author's Name Heung-Il Suk
1st Author's Affiliation Department of Computer Engineering, Pukyong National University()
2nd Author's Name Bong-Kee Sin
2nd Author's Affiliation Department of Computer Engineering, Pukyong National University
3rd Author's Name Beom-Joon Cho
3rd Author's Affiliation Department of Computer Engineering, Chosun University
Date 2007-10-26
Paper # PRMU2007-112
Volume (vol) vol.107
Number (no) 281
Page pp.pp.-
#Pages 6
Date of Issue