Séminaire du département Images et Signal du 07/11/2013 à 15h00

Noise-Adaptive Shape Reconstruction from Raw Point Sets

Intervenant : Simon Giraudot, INRIA - Sophia Antipolis Méditerranée

Lieu : Salle chartreuse

Résumé :

This seminar will be a presentation of an article published on Computer Graphics Forum for the EUROGRAPHICS Symposium on Geometry Processing 2013. It was granted with the 2nd Best Paper Award.

In this article, we propose a noise-adaptive shape reconstruction method specialized to smooth, closed shapes. Our algorithm takes as input a defect-laden point set with variable noise and outliers, and comprises three main steps. First, we compute a novel noise-adaptive distance function to the inferred shape, which relies on the assumption that the inferred shape is a smooth submanifold of known dimension. Second, we estimate the sign and confidence of the function at a set of seed points, through minimizing a quadratic energy expressed on the edges of a uniform random graph. Third, we compute a signed implicit function through a random walker approach with soft constraints chosen as the most confident seed points computed in previous step.

Le projet en question est sur cette page : https://team.inria.fr/titane/noise-adaptive-shape-reconstruction-from-raw-point-sets/