Chinese sign language recognition based on the Kinect
Yang Yon · Journal of Chongqing University of Posts and Telecommunications · 2013
A novel recognition method for Chinese sign language based on depth information extracted from the Microsoft Kinect is proposed in this paper.At first,the 3-D features of skeletons of mainbody and palms would be extracted based on Kinect.Secondly,the Chinese sign language can be seen composed by three components,that is,hand shape,location and hand orientation.The DBSCAN and K-means algorithms are used to extract the location subwords and orientation subwords respectively,a cluster ensemble method combined CLTree and Attribute bagging is proposed to extract the shape subwords.At last,the three subwords are combined together,and template matching method is used as a recognition method.The experimental results show that the average recognition rate is 90.35% on 72 Chinese signs,and the proposed method is proved to be effective.