Presentation 2008-06-19
Sign Language Recognition Based on Position and Movement Using Hidden Markov Model
Masaru MAEBATAKE, Masafumi NISHIDA, Yasuo HORIUCHI, Shingo KUROIWA,
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Abstract(in English) In sign language, the meaning of a word varies with hand positions. Thus, we studied on word recognition method integrated the position and movement of hands. The hand position was normalized for each utterance. We extracted the difference between frames as the movement from the position coordinate. The word recognition was performed using hidden Markov model based on these features. Furthermore, we assumed that the importance of the position and movement of hands changes with words and also performed the word recognition by the multi-stream HMM. As a result, recognition accuracy was 67.1% by using only hand position and was 79.9% by using both of the position and movement of hands. Moreover, we demonstrated that the importance of the movement was larger than the position by the multi-stream HMM.
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Keyword(in English) Sign Language / hand position / hand movement / hidden Markov model / mufti-stream
Paper # DE2008-2,PRMU2008-20
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Committee DE
Conference Date 2008/6/12(1days)
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Registration To Data Engineering (DE)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Sign Language Recognition Based on Position and Movement Using Hidden Markov Model
Sub Title (in English)
Keyword(1) Sign Language
Keyword(2) hand position
Keyword(3) hand movement
Keyword(4) hidden Markov model
Keyword(5) mufti-stream
1st Author's Name Masaru MAEBATAKE
1st Author's Affiliation Graduate School of Advanced Intergration Science, Chiba University()
2nd Author's Name Masafumi NISHIDA
2nd Author's Affiliation Graduate School of Advanced Intergration Science, Chiba University
3rd Author's Name Yasuo HORIUCHI
3rd Author's Affiliation Graduate School of Advanced Intergration Science, Chiba University
4th Author's Name Shingo KUROIWA
4th Author's Affiliation Graduate School of Advanced Intergration Science, Chiba University
Date 2008-06-19
Paper # DE2008-2,PRMU2008-20
Volume (vol) vol.108
Number (no) 93
Page pp.pp.-
#Pages 6
Date of Issue