Smooth surface reconstruction via natural neighbour interpolation of distance functions

By Jean-Daniel Boissonnat, Frédéric Cazals. SCG '00, 2000

410 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Graphics and Computer-Aided Design

View Paper: https://www.semanticscholar.org/paper/522771a87cffc0924ff37037989e45e9ee4d3822

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. Stanley J. Osher
2. Ronald Fedkiw
3. Leonidas J. Guibas
4. Niloy J. Mitra
5. Hongkai Zhao
6. Steve Y. Oudot
7. Jean-Daniel Boissonnat
8. Thomas Pock

In Computer Graphics and Computer-Aided Design

1. Stanley J. Osher
2. Ronald Fedkiw
3. Leonidas J. Guibas
4. Steve Y. Oudot
5. Jean-Daniel Boissonnat
6. Samrat Goswami
7. Tamal K. Dey
8. Niloy J. Mitra

Citations in the corpus

• Provable surface reconstruction from noisy samples (2004, methodology): “Some of these algorithms, following the work of Amenta and Bern [1], provide theoretical guarantees [2, 3, 6 , 13].”
• Provably good sampling and meshing of surfaces (2005, background): “– Reconstruction: several algorithms can reconstruct from E a surface that is homeomorphic [3, 4, 8, 19] or even ambient isotopic [5] to S.”
• Distributed Control of Robotic Networks (2009, background): “1981, Boissonnat and Cazals, 2002 ], are of particular interest to the treatment of this chapter because of their spatially-distributed computation character.”
• Tight cocone: a water-tight surface reconstructor (2003, background): “Boissonnat and Cazals [ 9 ] designed another algorithm based on natural neighbors following the development of CRUST.”
• A Globally Optimal Algorithm for Robust TV-L1 Range Image Integration (2007, background): “Combining several range images can be performed using general surface-from-point-clouds reconstruction algorithms (e.g. [15] [3] [1] [6]).”
• The 3D Model Acquisition Pipeline (2002, background): “Boissonnat and Cazals [64] use natural neighbor interpolation to define a global signed distance function.”
• Estimating surface normals in noisy point cloud data (2003, background): “Also some curve (or surface) reconstruction algorithms, as in [6], need to have the normal estimates as a part of the input data.”
• Fast surface reconstruction using the level set method (2001, methodology): “The second approach uses the data set to define a signed distance function on rectangular grids and denotes the zero isocontour of the signed distance function as the reconstructed implicit surface [5, 8 , 19].”