TY - JOUR
T1 - Hardware Based High Efficient Recognition of 3D Hand Gestures
AU - Yi Liang, Liang Zhuo, Ning Chen, Cheng Cheng, Ruizhi Li & Xinyan Gao
JO - Journal of Fiber Bioengineering and Informatics
VL - 2
SP - 337
EP - 345
PY - 2015
DA - 2015/08
SN - 8
DO - http://doi.org/10.3993/jfbim00106
UR - https://global-sci.org/intro/article_detail/jfbi/4714.html
KW - Gesture Recognition
KW - Human Computer Interaction
KW - Leap-motion
KW - CM1K
AB - 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.