Title
Geometric accuracy analysis for discrete surface approximation
Abstract
In geometric modeling and processing, computer graphics and computer vision, smooth surfaces are approximated by discrete triangular meshes reconstructed from sample points on the surfaces. A fundamental problem is to design rigorous algorithms to guarantee the geometric approximation accuracy by controlling the sampling density. This paper gives explicit formulae to the bounds of Hausdorff distance, normal distance and Riemannian metric distortion between the smooth surface and the discrete mesh in terms of principle curvature and the radii of geodesic circum-circle of the triangles. These formulae can be directly applied to design sampling density for data acquisitions and surface reconstructions. Furthermore, we prove that the meshes induced from the Delaunay triangulations of the dense samples on a smooth surface are convergent to the smooth surface under both Hausdorff distance and normal fields. The Riemannian metrics and the Laplace–Beltrami operators on the meshes are also convergent to those on the smooth surfaces. These theoretical results lay down the foundation for a broad class of reconstruction and approximation algorithms in geometric modeling and processing.
Year
DOI
Venue
2007
10.1016/j.cagd.2007.04.004
Computer Aided Geometric Design
Keywords
Field
DocType
Riemannian metric,Hausdorff distance,Normal distance,Delaunay triangulation,Principle curvature,Discrete mesh
Discrete geometry,Topology,Computational geometry,Geometric modeling,Principal curvature,Hausdorff distance,Voronoi diagram,Geodesic,Mathematics,Delaunay triangulation
Journal
Volume
Issue
ISSN
24
6
0167-8396
Citations 
PageRank 
References 
15
0.89
24
Authors
7
Name
Order
Citations
PageRank
Junfei Dai1322.13
Wei Luo2241.95
Miao Jin365035.98
Wei Zeng4844.97
Ying He51264105.35
Shing-tung Yau692592.69
Xianfeng Gu72997189.71