Real-time hand gesture recognition based on vision

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%. © 2010 Springer-Verlag Berlin Heidelberg.