Developing a Multiple-angle Hand Gesture Recognition System for Human Machine Interactions

This article presents a robotic visual system that allows effective recognition of multiple-angle hand gestures in finger guessing games. We shot images of hand gestures at various angles to train support vector machine (SVM) for the construction of a multiple-angle hand gesture recognition system. Our experimental results show that the hand gesture recognition system presented by this article can effectively recognize hand gestures, at over 95%, of different angles and sizes, with different ornaments, and of different skin colors, while recognizing right or left hand gestures, at up to 90% recognition rate.