Mutual information based gesture recognition

Authors:
Peter Harding;Michael Topsom;Nicholas Costen
Affiliations:
School of Computing, Mathematics and Digital Technology, Manchester Metropolitan University, UK;School of Computing, Mathematics and Digital Technology, Manchester Metropolitan University, UK;School of Computing, Mathematics and Digital Technology, Manchester Metropolitan University, UK
Venue:
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
Year:
2011

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Abstract

Proliferation of gestural interfaces necessitates the creation of robust gesture recognition systems. A novel technique using Mutual Information to classify gestures in a recognition system is presented. As this technique is based on well-known information theory metrics the underlying operation is not as complex as many other techniques which allows for this technique to be easily implemented. A high recognition rate of 98.55% was achieved, with recognition occurring in under 10ms.