(untitled) (Journal of Fiber Bioengineering and Informatics, 2015)
This paper addresses the technical issues related to hand gestures generation and their real-time recognition. The arbitrary 3D gestures are generated by the Leap-motion Controller which detects and tracks the hands and fingers to acquire position and motion information. We combine Leap-motion sensor and hardware based pattern engine to make gesture recognition easier and propose an efficient recognition solution involving a neuron chip (named CM1K). In our experiment, we used one-finger gesture cases to demonstrate the efficiency of our solution. Experimental results showed that our solution owns a high accuracy in gesture data acquiring and only costs a few milliseconds in recognizing speed. We also considered the situation of similar gestures recognition and analyzed the causes of low matching rate from specific data.