Human action recognition acts as an important role in human machine interaction. This paper proposes a human body recognition method from depth image based on part size and position features. Random forest classifiers are trained with different parameters. Experimental results demonstrate the feasibility of proposed approach. Recognition accuracy is about 91% and the computation time is about 0.96 us per pixel.