This paper presents an approach to reconstruct and optimize static 3D human body models using a single Kinect-like motion depth camera by moving the sensor freely around the human body. First, to reduce the noise in the depth data captured by the Kinect-like depth sensor, an approach is proposed to filter it according to the noise source created from the Kinect-like depth sensor. Then, the search for the corresponding patch is performed by combining with the information of depth and RGB, and the pair frames are aligned with the Gaussian mixture model and the improved signed distance function. For the loop closure problem, a closed curve fitting based method is provided with different layers to globally register all the frames. Finally, the human body surface is constructed by using the Poisson reconstruction. Experimental results show that the presented approach can reconstruct human models with high quality.