DUGi

Splat-based surface reconstruction from defect-laden point sets

http://dugi.udg.edu/item/http:@@@@hdl.handle.net@@10256@@10322

We introduce a method for surface reconstruction from point sets that is able to cope with noise and outliers. First, a splat-based representation is computed from the point set. A robust local 3D RANSAC-based procedure is used to filter the point set for outliers, then a local jet surface - a low-degree surface approximation - is fitted to the inliers. Second, we extract the reconstructed surface in the form of a surface triangle mesh through Delaunay refinement. The Delaunay refinement meshing approach requires computing intersections between line segment queries and the surface to be meshed. In the present case, intersection queries are solved from the set of splats through a 1D RANSAC procedure

This work was partially funded through MINECO under Grant CTM2010-15216, the EU under Grant FP7-ICT-2011-7-288704 and the European Research Council (ERC Starting Grant "Robust Geometry Processing", Grant Agreement No. 257474)

The authors thank the Stanford 3D Scanning Repository (Stanford University Computer Graphics Laboratory), Michael Kazhdan (Johns Hopkins University), the AIM@-SHAPE consortium (the ISTI-CNR Visual Computing Laboratory and Inria), Renaud Keriven and Jean-Philippe Pons for providing the models used in this paper. This work was partially funded through MINECO under Grant CTM2010-15216, the EU under Grant FP7-ICT-2011-7-288704 and the European Research Council (ERC Starting Grant "Robust Geometry Processing", Grant Agreement No. 257474)

info:eu-repo/grantAgreement/EC/FP7/288704/EU/Marine robotic system of self-organizing, logically linked physical nodes/MORPH

Elsevier