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