Presentation 2004/3/19
Sign Language Recognition Using Gesture Component Involved Transition Part
Yuji OKAZAWA, Masafumi NISHIDA, Yasuo HORIUCHI, AKira ICHIKAWA,
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Abstract(in English) In conventional sign language recognition, methods which recognize a gesture component such as hand form and position and integrate the recognition results have proposed. However, it is necessary to process a transition between sign words in order to recognize a continuous sign language. In the conventional method, there is a problem that a number of models increases so much because the gesture component and transition are modeled separately. Thus, we propose a method which models and recognize by combining the gesture component and transition using hidden Markov model (HMM). We carried out a recognition experiment using eleven gesture component. As a result, a recognition accuracy improved 30% by the proposed method compared with the conventional method.
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Keyword(in English) Sign Language Recognition / Gesture Component / Transition / Hidden Markov Model
Paper # WIT2003-65
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Committee WIT
Conference Date 2004/3/19(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Sign Language Recognition Using Gesture Component Involved Transition Part
Sub Title (in English)
Keyword(1) Sign Language Recognition
Keyword(2) Gesture Component
Keyword(3) Transition
Keyword(4) Hidden Markov Model
1st Author's Name Yuji OKAZAWA
1st Author's Affiliation Graduate School of Science and Technology Chiba University()
2nd Author's Name Masafumi NISHIDA
2nd Author's Affiliation Graduate School of Science and Technology Chiba University
3rd Author's Name Yasuo HORIUCHI
3rd Author's Affiliation Graduate School of Science and Technology Chiba University
4th Author's Name AKira ICHIKAWA
4th Author's Affiliation Graduate School of Science and Technology Chiba University
Date 2004/3/19
Paper # WIT2003-65
Volume (vol) vol.103
Number (no) 747
Page pp.pp.-
#Pages 6
Date of Issue