Application of neural networks in spatio-temporal hand gesture recognition

Mu Chun Su, Hi Huang, Chia Hsien Lin, Chen Lee Huang, Chi Da Lin

Research output: Contribution to conferencePaperpeer-review

8 Scopus citations

Abstract

Several successful approaches to spatio-temporal signal processing such as speech recognition and hand gesture recognition have been proposed. Most of them involve time alignment which requires substantial computation and considerable memory storage. In this paper, we present a neural-network-based approach to spatio-temporal pattern recognition. This approach employs a powerful method based on HyperRectangular Composite Neural Networks (HRCNNs) for selecting templates, therefor, considerable memory is alleviated. In addition, it greatly reduces substantial computation in the matching process because it obviates time alignment. Two databases consisted of 51 spatio-temporal hand gestures were utilized for verifying its performance. An encouraging experimental result confirmed the effectiveness of the proposed method.

Original languageEnglish
Pages2116-2121
Number of pages6
StatePublished - 1998
EventProceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3) - Anchorage, AK, USA
Duration: 4 May 19989 May 1998

Conference

ConferenceProceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3)
CityAnchorage, AK, USA
Period4/05/989/05/98

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