Real-time hand gesture recognition based on vision

Authors:
Yu Ren;Chengcheng Gu
Affiliations:
Institute of Intelligent and Software Technology, Hangzhou Dianzi University, Hangzhou, China;Institute of Intelligent and Software Technology, Hangzhou Dianzi University, Hangzhou, China
Venue:
Edutainment'10 Proceedings of the Entertainment for education, and 5th international conference on E-learning and games
Year:
2010

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Abstract

In vision-based hand gesture recognition, an accurate description of gestures and a proper classifier which is chosen for classifying will bring great effect on the result of classification. In this paper, we choose Normalized Moment of Inertia (NMI) and Hu invariant moments of gesture pictures as the features of gestures, and Support Vector Machine (SVM) as the classifier. We experiment the method on eight gestures after training, and get an ideal accuracy of gesture recognition which closes to 97%.