Presentation | 2005/5/13 Segmentation of Sign Language for making HMM Kana KAWAHIGASHI, Yoshiaki SHIRAI, Nobutaka SHIMADA, Jun MIURA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In this paper, HMM is made by extracting hand features of position and shape, and sign language is recognized. When face and hands are overlapped, hands regions are extracted by considering occlusion. Appropriate features of hands are extracted from hands region. In training phase, image sequences are segmented automatically to decide the number of the states. The experimental result is shown for recognition using HMM. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Sign Language / HMM / State / Feature Extraction |
Paper # | WIT2005-21 |
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Committee | WIT |
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Conference Date | 2005/5/13(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Registration To | Well-being Information Technology(WIT) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Segmentation of Sign Language for making HMM |
Sub Title (in English) | |
Keyword(1) | Sign Language |
Keyword(2) | HMM |
Keyword(3) | State |
Keyword(4) | Feature Extraction |
1st Author's Name | Kana KAWAHIGASHI |
1st Author's Affiliation | Department of Mechanical Systems Graduated School of Engineering Osaka University() |
2nd Author's Name | Yoshiaki SHIRAI |
2nd Author's Affiliation | Department of human and Computer Intelligence Ritsumeikan University |
3rd Author's Name | Nobutaka SHIMADA |
3rd Author's Affiliation | Department of human and Computer Intelligence Ritsumeikan University |
4th Author's Name | Jun MIURA |
4th Author's Affiliation | Department of Mechanical Systems Graduated School of Engineering Osaka University |
Date | 2005/5/13 |
Paper # | WIT2005-21 |
Volume (vol) | vol.105 |
Number (no) | 67 |
Page | pp.pp.- |
#Pages | 6 |
Date of Issue |