Partly-Hidden Markov model and its application to gesture recognition

Tetsunori Kobayashi*, Satoshi Haruyama

*この研究の対応する著者

研究成果: Conference article査読

38 被引用数 (Scopus)

抄録

A new pattern matching method, Partly-Hidden Markov model, is proposed for gesture recognition. Hidden Markov Model, which is widely used for the time series pattern recognition, can deal with only piecewise stationary stochastic 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 results of 6 sign-language recognition test, the error rate was improved by 73% compared with normal HMM.

本文言語English
ページ(範囲)3081-3084
ページ数4
ジャーナルICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
4
出版ステータスPublished - 1997 1 1
イベントProceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 5) - Munich, Ger
継続期間: 1997 4 211997 4 24

ASJC Scopus subject areas

  • ソフトウェア
  • 信号処理
  • 電子工学および電気工学

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