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

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)515-519
Number of pages5
JournalProceedings - International Conference on Pattern Recognition
Volume16
Issue number2
DOIs
Publication statusPublished - 2002 Jan 1

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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