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A method is presented for recognizing hand gestures by using a sequence of real-time depth image data acquired by an active sensing hardware. Hand posture and motion information extracted from a video is represented in a gesture space which consists of a number of aspects including hand shape, location and motion information. In this space, it is shown to be possible to recognize many types of gestures. Experimental results are shown to validate our approach and characteristics of our approach are discussed.