Extension of hidden markov models to deal with multiple candidates of observations and its application to mobile-robot-oriented gesture recognition

Yosuke Sato, Tetsunori Kobayashi

研究成果: Article

9 引用 (Scopus)

抜粋

We propose a modified Hidden Markov Model (HMM) with a view to improving gesture recognition in the moving camera condition. We define a new gesture recognition framework in which multiple candidates of feature vectors are generated with confidence measures and the HMM is extended to deal with these multiple feature vectors. Experimental analysis comparing the proposed system with feature vectors based on DCT and the method of selecting only one candidate feature point verify the effectiveness of the technique.

元の言語English
ページ(範囲)515-519
ページ数5
ジャーナルProceedings - International Conference on Pattern Recognition
16
発行部数2
DOI
出版物ステータスPublished - 2002 1 1

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ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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