Abstract : To achieve geometric reconstruction from 3D datasets two complementary approaches have been widely used. On one hand the deformable model framework locally applies forces to fit the data. On the other hand, the non-rigid registration framework computes a global transformation minimizing the distance between a template and the data. We first show that applying a global transformation on a surface template, is equivalent to applying certain global forces on a deformable model. Second we propose a scheme which combines the registration and free-form deformation. This globally constrained deformation model allows us to control the amount of deformation from the reference shape with a single parameter. Finally, we propose a general algorithm for performing model-based reconstruction in a robust and accurate manner. Examples on both range data and medical images are used to illustrate and validate the globally constrained deformation framework.
https://hal.inria.fr/inria-00615089
Contributeur : Project-Team Asclepios
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Soumis le : mercredi 17 août 2011 - 23:34:38
Dernière modification le : samedi 27 janvier 2018 - 01:31:49
Document(s) archivé(s) le : vendredi 25 novembre 2011 - 11:30:34
Johan Montagnat, Hervé Delingette. Globally constrained deformable models for 3D object reconstruction. Signal Processing, Elsevier, 1998, 71 (2), pp.173--186. 〈inria-00615089〉
