Abstract
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.
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Lamovsky, D. (2012). Semi-variational Registration of Range Images by Non-rigid Deformations. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P., Zemčík, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2012. Lecture Notes in Computer Science, vol 7517. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33140-4_31
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DOI: https://doi.org/10.1007/978-3-642-33140-4_31
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