|Denis V. Lamovsky|
We present a semi-variational approach for accurate registration of a set of range images. For each range image we estimate a transformation composed of a similarity and a free-form deformation in order to obtain a smoothly stitched surface. The resulting three-dimensional model has no jumps or sharp transitions in the place of stitching. We use the presented approach for accurate human head reconstruction from a set of facets subsequently captured from different views and computed independently. A joint energy for both types of transformations is formulated, which involves several regularization constraints defined according to a specification of the resulting surface. A strategy for reweighting the impact of correspondences is presented to improve stability and convergence of the approach. We demonstrate the applicability of our method on several representative examples.