Hand Gesture Recognition Based on Dynamic Bayesian Network Framework(Internationa Session 5)

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概要

• 論文の詳細を見る

• 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.

• 社団法人電子情報通信学会の論文
• 2007-10-18

著者

• Cho Beom-joon

  Department Of Computer Engineering Chosun University

• Suk Heung-Il

  Department of Computer Engineering, Pukyong National University

• Sin Bong-Kee

  Department of Computer Engineering, Pukyong National University

• Sin Bong-kee

  Department Of Computer Engineering Pukyong National University

• Suk Heung-il

  Department Of Computer Engineering Pukyong National University

関連論文

• Hand Gesture Recognition Based on Dynamic Bayesian Network Framework(Internationa Session 5)

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