Multigrid convergent principal curvature estimators in digital geometry

被引：27

作者：

Coeurjolly, David ^{[1
]}

Lachaud, Jacques-Olivier ^{[2
,3
]}

Levallois, Jeremy ^{[1
,2
]}

机构：

[1] Univ Lyon, CNRS, INSA Lyon, LIRIS,UMR5205, F-69621 Villeurbanne, France

[2] Univ Savoie, CNRS, LAMA, UMR 5127, F-73776 Chambery, France

[3] Univ Grenoble Alpes, CNRS, LJK, UMR 5224, F-38041 Grenoble, France

来源：

COMPUTER VISION AND IMAGE UNDERSTANDING | 2014年 / 129卷

关键词：

Digital geometry; Curvature estimation; Multigrid convergence; Integral invariants; LARGE CONVEX-BODIES; LATTICE POINTS; CONVOLUTIONS; SURFACES; FEATURES;

D O I：

10.1016/j.cviu.2014.04.013

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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. (C) 2014 Elsevier Inc. All rights reserved.

引用

页码：27 / 41

页数：15

共 46 条

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[3]

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[4]

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