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Article Dans Une Revue Signal Processing Année : 1998

Globally constrained deformable models for 3D object reconstruction

Résumé

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.
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Dates et versions

inria-00615089 , version 1 (17-08-2011)

Identifiants

  • HAL Id : inria-00615089 , version 1

Citer

Johan Montagnat, Hervé Delingette. Globally constrained deformable models for 3D object reconstruction. Signal Processing, 1998, 71 (2), pp.173--186. ⟨inria-00615089⟩
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