Implicit Surface Reconstruction and Feature Detection with a Learning Algorithm

We propose a new algorithm for implicit surface reconstruction and feature detection. The algorithm is based on a self organising map with the connectivity of a regular 3D grid that can be trained into an implicit representation of surface data. The implemented self organising map stores not only its current state but also its recent training history which can be used for feature detection. Preliminary results show that the proposed algorithm gives good quality reconstructions and can detect various types of feature.

[1]  Hans-Peter Seidel,et al.  Using growing cell structures for surface reconstruction , 2003, 2003 Shape Modeling International..

[2]  Tamal K. Dey,et al.  Tight cocone: a water-tight surface reconstructor , 2003, SM '03.

[3]  William E. Lorensen,et al.  Marching cubes: A high resolution 3D surface construction algorithm , 1987, SIGGRAPH.

[4]  Tony DeRose,et al.  Surface reconstruction from unorganized points , 1992, SIGGRAPH.

[5]  Marshall W. Bern,et al.  A new Voronoi-based surface reconstruction algorithm , 1998, SIGGRAPH.

[6]  Daniel Cohen-Or,et al.  Eurographics Symposium on Geometry Processing (2007) Data-dependent Mls for Faithful Surface Approximation , 2022 .

[7]  Hans-Peter Seidel,et al.  Multi-level partition of unity implicits , 2005, SIGGRAPH Courses.

[8]  Hans-Peter Seidel,et al.  Fast and robust detection of crest lines on meshes , 2005, SPM '05.

[9]  Seungyong Lee,et al.  Self-Organising Maps for Implicit Surface Reconstruction , 2008, TPCG.

[10]  D. Cohen-Or,et al.  Robust moving least-squares fitting with sharp features , 2005, ACM Trans. Graph..

[11]  Richard K. Beatson,et al.  Reconstruction and representation of 3D objects with radial basis functions , 2001, SIGGRAPH.

[12]  Teuvo Kohonen,et al.  Self-organized formation of topologically correct feature maps , 2004, Biological Cybernetics.

[13]  Anath Fischer,et al.  Adaptive reconstruction of freeform objects with 3D SOM neural network grids , 2001, Proceedings Ninth Pacific Conference on Computer Graphics and Applications. Pacific Graphics 2001.