Convergent Geometric Estimators with Digital Volume and Surface Integrals
Apr 18, 2016·
·
0 min read
Jacques-Olivier Lachaud

Abstract
This talk presents several methods to estimate geometric quantities on subsets of the digital space Zd. We take an interest both on global geometric quantities like volume and area, and on local geometric quantities like normal and curvatures. All presented methods have the common property to be multigrid convergent, i.e. the estimated quantities tend to their Euclidean counterpart on ner and ner digitizations of (smooth enough) Euclidean shapes. Furthermore, all methods rely on digital integrals, which approach either volume integrals or surface integrals along shape boundary. With such tools, we achieve multigrid convergent estimators of volume, moments and area in Zd, of normals, curvature and curvature tensor in Z2 and Z3, and of covariance measure and normals in Zd even with Hausdorff noise.
Date
Apr 18, 2016 9:00 AM — 10:00 AM
Event
Location
Nantes, France
Talk
Digital Geometry
Volume Estimation
Moment Estimation
Normal Estimation
Curvature Estimation
Area Estimation
Multigrid Convergence
Digital Integration
Integral Invariants
Digital Moments
Voronoi Covariance Measure
Stability
Authors
Professor of Computer Science
My research interests include digital geometry, geometry processing, image analysis, variational models and discrete calculus.