Hardware Based High Efficient Recognition of 3D Hand Gestures

Abstract

This paper addresses the technical issues related to hand gestures generation and their real-time\r recognition. The arbitrary 3D gestures are generated by the Leap-motion Controller which detects\r and tracks the hands and fingers to acquire position and motion information. We combine Leap-motion\r sensor and hardware based pattern engine to make gesture recognition easier and propose an efficient\r recognition solution involving a neuron chip (named CM1K). In our experiment, we used one-finger\r gesture cases to demonstrate the efficiency of our solution. Experimental results showed that our solution\r owns a high accuracy in gesture data acquiring and only costs a few milliseconds in recognizing speed.\r We also considered the situation of similar gestures recognition and analyzed the causes of low matching\r rate from specific data.