Reconstructing 3D human models with a Kinect

Three‐dimensional human model reconstruction has wide applications due to the rapid development of computer vision. The appearance of cheap depth camera, such as Kinect, opens up new horizons for home‐oriented 3D human reconstructions. However, the resolution of Kinect is relatively low, making it difficult to build accurate human models. In this paper, we improve the accuracy of human model reconstruction from two aspects. First, we improve the depth data quality by registering the depth images captured from multi‐views with a single Kinect. The part‐wise registration method and implicit‐surface‐based de‐noising method are proposed. Second, we utilize a statistical human model to iteratively augment and complete the human body information by fitting the statistical human model to the registered depth image. Experimental results and several applications demonstrate the applicability and quality of our system, which can be potentially used in virtual try‐on systems. Copyright © 2015 John Wiley & Sons, Ltd. In this paper, we provide a method of reconstructing 3D naked human models for human bodies or dressed humans using the depth images captured by a single Kinect. The depth images from multi‐views are part‐wisely registered together, and implicit‐surface‐based de‐noising method is put forward for the coarse data. Afterwards, we fit a statistical model to the registered depth image iteratively in order to obtain the reconstructed 3D human model and apply the reconstructed models in virtual try‐on systems.