Partly-Hidden Markov model and its application to gesture recognition

Tetsunori Kobayashi, Satoshi Haruyama

研究成果: Conference article

37 引用 (Scopus)

抜粋

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.

元の言語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
出版物ステータス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

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ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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