research-article

Elliptic Gabriel Taubin smoothing of point clouds▪

Authors:

Alexander Agathos,

Philip Azariadis,

Sofia KyratziAuthors Info & Claims

Volume 106, Issue C

Pages 20 - 32

https://doi.org/10.1016/j.cag.2022.05.009

Published: 01 August 2022 Publication History

Abstract

A point cloud smoothing algorithm is presented which is based on the mesh filtering procedure of Taubin. This is accomplished by defining a robust one-ring neighborhood for each vertex of the point cloud based on the elliptic Gabriel graph and by incorporating non-uniform Gaussian weights during the smoothing process. The proposed method is robust to noise and very simple to implement. It is able to produce high quality smoothed point clouds that avoid the shrinkage, point clustering and edge over-smoothing problems, without the use of normal information which is computationally unstable on noisy point sets. Through an extensive comparison with state-of-the-art smoothing methods the advantages of the proposed method in both free-form and CAD-oriented models are presented. A framework for efficient GPU implementation is also provided. The proposed method is able to process more than 15 million points in about 20 secs making it very suitable for point sets produced by modern 3D scanners.

Graphical abstract

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Highlights

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A new efficient point-cloud smoothing algorithm.

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A GPGPU implementation able to handle hundreds of thousands or millions of points.

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An extensive comparison with state-of-the-art point-cloud filtering methods.

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Cited By

Agathos AAzariadis P(2024)Multi-GPU 3D k-nearest neighbors computation with application to ICP, point cloud smoothing and normals computationParallel Computing10.1016/j.parco.2024.103093121:COnline publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1016/j.parco.2024.103093
Wang WPan WLiu XSu KRolfe BLu X(2024)Random screening-based feature aggregation for point cloud denoisingComputers and Graphics10.1016/j.cag.2023.08.013116:C(64-72)Online publication date: 4-Mar-2024
https://dl.acm.org/doi/10.1016/j.cag.2023.08.013
Xiao DShi ZWang B(2024)Alternately denoising and reconstructing unoriented point setsComputers and Graphics10.1016/j.cag.2023.08.011116:C(139-149)Online publication date: 4-Mar-2024
https://dl.acm.org/doi/10.1016/j.cag.2023.08.011
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Elliptic Gabriel Taubin smoothing of point clouds▪

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Information

Published In

cover image Computers and Graphics

Computers and Graphics Volume 106, Issue C

Aug 2022

305 pages

ISSN:0097-8493

Issue’s Table of Contents

Elsevier Ltd.

Publisher

Pergamon Press, Inc.

United States

Publication History

Published: 01 August 2022

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Cited By

Agathos AAzariadis P(2024)Multi-GPU 3D k-nearest neighbors computation with application to ICP, point cloud smoothing and normals computationParallel Computing10.1016/j.parco.2024.103093121:COnline publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1016/j.parco.2024.103093
Wang WPan WLiu XSu KRolfe BLu X(2024)Random screening-based feature aggregation for point cloud denoisingComputers and Graphics10.1016/j.cag.2023.08.013116:C(64-72)Online publication date: 4-Mar-2024
https://dl.acm.org/doi/10.1016/j.cag.2023.08.013
Xiao DShi ZWang B(2024)Alternately denoising and reconstructing unoriented point setsComputers and Graphics10.1016/j.cag.2023.08.011116:C(139-149)Online publication date: 4-Mar-2024
https://dl.acm.org/doi/10.1016/j.cag.2023.08.011
(2023)Editor’s Choice Award 2022Computers and Graphics10.1016/j.cag.2023.12.005117:C(A3)Online publication date: 1-Dec-2023
https://dl.acm.org/doi/10.1016/j.cag.2023.12.005
Agathos AAzariadis P(2023)Optimal Point-to-Point geodesic path generation on point cloudsComputer-Aided Design10.1016/j.cad.2023.103552162:COnline publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1016/j.cad.2023.103552
Jorge J(2022)Editorial noteComputers and Graphics10.1016/j.cag.2022.07.012106:C(A1-A3)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1016/j.cag.2022.07.012

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