Fitting Geometrical Deformable Models to Registered Range Images

In this paper we present a method for adapting a geometrical deformable model (GDM) to a set of registered range images in order to reconstruct real-world objects from multiple range images. Our approach registers the range images simultaneously, carves out an intermediate volume and finally generates an accurate, sparse triangle mesh. The proposed GDM scheme refines an initial roughly approximated mesh by deformation and adaptive subtriangulation. Even in the case of very large data sets our approach presents an efficient method of surface reconstruction due to adaptive improvement to the desired degree of accuracy. Since the root mean square approximation error of each triangle is minimized in an iterative procedure, the mesh quality is higher than that of previous approaches.