A new system, DeepHand, uses a “convolutional neural network” that mimics the human brain and is capable of “deep learning” to understand the hand’s nearly endless complexity of joint angles and contortions.
“We figure out where your hands are and where your fingers are and all the motions of the hands and fingers in real time,” Ramani said.
A research paper about DeepHand will be presented during CVPR 2016, a computer vision conference in Las Vegas from Sunday (June 26 )to July 1 (http://cvpr2016.thecvf.com/).
DeepHand uses a depth-sensing camera to capture the user’s hand, and specialized algorithms then interpret hand motions. (A YouTube video is available at https://youtu.be/ScXCqC2SNNQ)
See the full story here; http://www.purdue.edu/newsroom/releases/2016/Q2/new-tool-for-virtual-and-augmented-reality-uses-deep-learning.html