Volumetric template fitting for human body reconstruction from incomplete data

In this paper, we present a method for reconstructing 3D human body from incomplete data, which are point clouds captured by inexpensive RGB-D cameras. Making use of the volumetric mesh in a template, the fitting process is robust. This method produces high quality fitting results on incomplete data, which are hard to be offered by the surface fitting based methods. The method is formulated as an optimization procedure, so that the results of volumetric fitting rely on the quality of initial shape (i.e., the shape of template). In order to find a good initial shape, we develop a template selection algorithm to choose a template in an iterative manner by using the statistical models of human bodies. Experimental results show that our method can successfully reconstruct human body with good quality to be used in design and manufacturing applications.