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In this paper, we propose a novel three-dimensional combining features method for sign language recognition. Based on the Kinect depth data and the skeleton joints data, we acquire the 3D trajectories of right hand, right wrist and right elbow. To construct feature vector, the paper uses combining location and spherical coordinate feature representation.(More)
An important part for sign language expression is hand shape, and the 3D hand motion trajectories also contain abundant information to interpret the meaning of sign language. In this paper, a novel feature descriptor is proposed for sign language recognition, the hand shape features extracted from the depth images and spherical coordinate (SPC) feature(More)
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