Hand Gesture Recognition Using Fast Multi-scale Analysis

Hand gesture has been used as a natural and efficient way in human computer interaction. Due to independence of auxiliary input devices, vision-based hand interfaces is more favorable for users. However, the process of hand gesture recognition is very time consuming, which often brings much frustration to users. In this paper, we propose a fast feature detection and description approach which can significantly speed up hand gesture recognition. Firstly, integral image is used to approximate Gaussian derivatives to calculate image convolution in feature detection. Then multi-scale geometric descriptors at feature points are obtained to represent hand gestures. Finally gesture is recognized with its geometric configuration. Experiments show that the proposed method needs much less time consumption while obtains comparative performance with its counterpart in literatures.