Supervised training based hand gesture recognition system

Attila Licsár, Tamás Szirányi

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

We have developed a hand gesture recognition system, based on the shape analysis of static gestures, for Human Computer Interaction purposes. Our appearance-based recognition uses modified Fourier descriptors for the classification, of hand shapes. As always found in literature, such recognition systems consist of two phases: training and recognition. In our new practical approach, following the chosen appearance-based model, training and recognition is done in an interactive supervised way: the adaptation for untrained gestures is also solved by hand signals. Our experimental results with three different users are reported. In this paper, besides describing the recognition itself, we demonstrate our interactive training method in a practical application.

Original languageEnglish
Pages (from-to)999-1002
Number of pages4
JournalProceedings - International Conference on Pattern Recognition
Volume16
Issue number3
Publication statusPublished - Dec 1 2002

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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