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Skeleton-Based Dynamic Hand Gesture Recognition
2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
In this paper, a new skeleton-based approach is proposed for 3D hand gesture recognition. Specifically, we exploit the geometric shape of the hand to extract an effective descriptor from hand skeleton connected joints returned by the Intel RealSense depth camera. Each descriptor is then encoded by a Fisher Vector representation obtained using a Gaussian Mixture Model. A multi-level representation of Fisher Vectors and other skeleton-based geometric features is guaranteed by a temporal pyramiddoi:10.1109/cvprw.2016.153 dblp:conf/cvpr/SmedtWV16 fatcat:sgmcym5rsbgr5fbvhw6odfmb2y