Presentation | 1998/1/22 Partly-Hidden Markov Model and Its Application to Gesture Recognition Ken Masumitsu, Tetunori Kobayashi, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | A new pattern matching method, Partly-Hidden Markov model, is proposed for gesture recognition. HMM, which has been used for time series pattern matting, can deal with only piecewise stationary process. We solved this problem by introducing the modified second order Markov Model, in which the first state is hidden and the second one is observable. As the result of 6 hand sign language recognition, the error rate iwas improved by 43% compared with HMM. And as for the simple feature parameter condition, PHMM achived 60% less error rate than HMM. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | HMM / gesture recognition / sign language |
Paper # | PRMU97-203 |
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Committee | PRMU |
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Conference Date | 1998/1/22(1days) |
Place (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Pattern Recognition and Media Understanding (PRMU) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Partly-Hidden Markov Model and Its Application to Gesture Recognition |
Sub Title (in English) | |
Keyword(1) | HMM |
Keyword(2) | gesture recognition |
Keyword(3) | sign language |
1st Author's Name | Ken Masumitsu |
1st Author's Affiliation | Department of Electrical, Electronics & Computer Engineering Waseda University() |
2nd Author's Name | Tetunori Kobayashi |
2nd Author's Affiliation | Department of Electrical, Electronics & Computer Engineering Waseda University |
Date | 1998/1/22 |
Paper # | PRMU97-203 |
Volume (vol) | vol.97 |
Number (no) | 500 |
Page | pp.pp.- |
#Pages | 8 |
Date of Issue |