@Article{JFBI-8-337, author = {}, title = {Hardware Based High Efficient Recognition of 3D Hand Gestures}, journal = {Journal of Fiber Bioengineering and Informatics}, year = {2015}, volume = {8}, number = {2}, pages = {337--345}, abstract = {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.}, issn = {2617-8699}, doi = {https://doi.org/10.3993/jfbim00106}, url = {http://global-sci.org/intro/article_detail/jfbi/4714.html} }