Anisotropic smoothing of point sets,

By Carsten E. M. C. Lange, Konrad Polthier. 2005

168 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Graphics and Computer-Aided Design

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

In Computer Graphics and Computer-Aided Design

Citations in the corpus

PCPNet Learning Local Shape Properties from Raw Point Clouds (2017, methodology): “Several such techniques rely on estimating the normals ﬁrst and then robustly ﬁtting oriented curvatures [HM02, LP05], which in turn lead to estimates of principal curvature values.”
State of research in automatic as-built modelling (2015, methodology): “The filtering proposed in [77] uses mean curvature flows to perform anisotropic filtering of point clouds, but”
Voronoi-based variational reconstruction of unoriented point sets (2007, unknown): “Normal estimation from point sets has received a lot of attention in the past few years (see e.g., [PKKG03,MNG04, DLS05,OF05, LP05 ,HXMP05]).”
Scale Space Meshing of Raw Data Point Sets (2011, background): “Another possibility is to adapt the curvature estimation of [Tau95] to the case of point clouds, like in [LP05].”
A review of algorithms for filtering the 3D point cloud (2017, unknown): “Extending Taubin’s work [76], Lange and Polthier [77] took the directional curvatures, principal curvatures and the Weingarten map into account to obtain an anisotropic geometric mean curvature flow method to filter point cloud.”
Consolidation of unorganized point clouds for surface reconstruction (2009, methodology): “There are also algorithms for point cloud smoothing [Lange and Polthier 2005] and simplification [Pauly et al.”
Extracting lines of curvature from noisy point clouds (2009, background): “Surface derivatives such as normal and curvature are as important as surface position for the perception, understanding, interrogation of shape (30; 26), registration (42), smoothing (27) and symmetry detection (34) to name a few applications.”
Voronoi-Based Curvature and Feature Estimation from Point Clouds (2011, background): “…are rotation-invariant local descriptors, which together with principal curvature directions have proven useful in detecting structural regularity [PMW + 08], global matching [AMCO08], modeling and rendering of point-based surfaces [GTE + 06], and anisotropic smoothing [LP05] to name just a few.”
Manifold Denoising (2006, methodology): “Since then several modifications of his original idea have been proposed in the computer graphics community, including the recent development in [11] to apply the algorithm directly to point cloud data inR(3).”