Best data-dependent triangulations
type: Item
instance of: scholarly article
title: Best data-dependent triangulations
zbMATH Open document ID: 0970.65015
DOI: 10.1016/S0377-0427(00)00368-X
author: Lyuba Alboul
author: G. Kloosterman
author: Cornelis Traas
author: Ruud van Damme
published in: Journal of Computational and Applied Mathematics
publication date: 2000-08-14T00:00:00Z
review text: The first step in evaluation a surface is to construct a triangulation of the data. A ``good'' triangulation can help to solve many problems, i.e., in scattered data interpolation and approximation, or in applications recovering 3-D objects. Therefore, in this paper, as a measure of the quality of triangulation methods various differential geometrical properties, namely integral absolute Gaussian curvature, integral absolute mean curvature and area are considered. A comparison is made with data-dependent triangulation methods existing in the literature. The most promising criterion seems to be minimizing absolute mean curvature.
reviewed by: Heiner Mühlig
Mathematics Subject Classification ID: 65D17
Mathematics Subject Classification ID: 53C42
zbMATH DE Number: 1491246
zbMATH Keywords: surface reconstruction
zbMATH Keywords: triangulations
zbMATH Keywords: scattered data interpolation
zbMATH Keywords: Gaussian curvature
zbMATH Keywords: absolute mean curvature
MaRDI profile type: Publication
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description: scientific article; zbMATH DE number 1491246