Multigrid convergent principal curvature estimators in digital geometry - Physics, Radiobiology, Medical Imaging, and Simulation (PRIMES)
Journal Articles Computer Vision and Image Understanding Year : 2014

Multigrid convergent principal curvature estimators in digital geometry

Abstract

In many geometry processing applications, the estimation of differential geometric quantities such as curvature or normal vector field is an essential step. In this paper, we investigate a new class of estimators on digital shape boundaries based on integral invariants (Pottmann et al., 2007) [39]. More precisely, we provide both proofs of multigrid convergence of principal curvature estimators and a complete experimental evaluation of their performances.
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Dates and versions

hal-01119434 , version 1 (20-05-2024)

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David Coeurjolly, Jacques-Olivier Lachaud, Jérémy Levallois. Multigrid convergent principal curvature estimators in digital geometry. Computer Vision and Image Understanding, 2014, 129 (1), pp.27-41. ⟨10.1016/j.cviu.2014.04.013⟩. ⟨hal-01119434⟩
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