This paper presents a method for hand gesture recognition based on 3D point cloud. Digital image\nprocessing technology is used in this research. Based on the 3D point from depth camera, the system\nfirstly extracts some raw data of the hand. After the data segmentation and preprocessing,\nthree kinds of appearance features are extracted, including the number of stretched fingers, the\nangles between fingers and the gesture region�s area distribution feature. Based on these features,\nthe system implements the identification of the gestures by using decision tree method. The results\nof experiment demonstrate that the proposed method is pretty efficient to recognize common\ngestures with a high accuracy.
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