Adaptive and deformable models based on simplex meshes

Simplex meshes are simply-connected meshes that are topologically the dual of triangulations. We have introduced a simplex mesh representation for recognizing partially-occluded smooth objects. In this paper, we present a physically-based approach for recovering 3D objects, based on the geometry of simplex meshes. Elastic behavior is modelled by local stabilizing functionals controlling the mean curvature through the simplex angle extracted at each vertex. Those functionals are viewpoint-invariant, intrinsic and scale-sensitive. Unlike deformable surfaces defined on regular grids, simplex meshes are highly adaptive structures, and we have developed a refinement process for increasing the mesh resolution at highly curved or inaccurate parts. End contours are created in a semi-automatic way. Finally, operations for connecting simplex meshes are performed to recover complex models from parts of simpler shapes.<<ETX>>

[1]  Hervé Delingette,et al.  Simplex meshes: a general representation for 3D shape reconstruction , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[2]  Katsushi Ikeuchi,et al.  Shape representation and image segmentation using deformable surfaces , 1992, Image Vis. Comput..

[3]  Katsushi Ikeuchi,et al.  A spherical representation for the recognition of curved objects , 1993, 1993 (4th) International Conference on Computer Vision.

[4]  Demetri Terzopoulos,et al.  A finite element model for 3D shape reconstruction and nonrigid motion tracking , 1993, 1993 (4th) International Conference on Computer Vision.

[5]  Demetri Terzopoulos,et al.  Adaptive meshes and shells: irregular triangulation, discontinuities, and hierarchical subdivision , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[6]  Tony DeRose,et al.  Mesh optimization , 1993, SIGGRAPH.

[7]  F. Leitner Segmentation dynamique d'images tridimensionnelles , 1993 .

[8]  Katsushi Ikeuchi,et al.  Shape representation and image segmentation using deformable surfaces , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[9]  ISAAC COHEN,et al.  Using deformable surfaces to segment 3-D images and infer differential structures , 1992, CVGIP Image Underst..