Parameter-Free and Improved Connectivity for Point Clouds
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Date
2023
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Determining connectivity in unstructured point clouds is a long-standing problem that is still not addressed satisfactorily. In this poster, we propose an extension to the proximity graph introduced in [MOW22] to three-dimensional models. We use the spheres-of-influence (SIG) proximity graph restricted to the 3D Delaunay graph to compute connectivity between points. Our approach shows a better encoding of the connectivity in relation to the ground truth than the k-nearest neighborhood (kNN) for a wide range of k values, and additionally, it is parameter-free. Our result for this fundamental task offers potential for many applications relying on kNN, e.g., improvements in normal estimation, surface reconstruction, motion planning, simulations, and many more.
Description
CCS Concepts: Computing methodologies -> Point-based models
@inproceedings{10.2312:egp.20231023,
booktitle = {Eurographics 2023 - Posters},
editor = {Singh, Gurprit and Chu, Mengyu (Rachel)},
title = {{Parameter-Free and Improved Connectivity for Point Clouds}},
author = {Marin, Diana and Ohrhallinger, Stefan and Wimmer, Michael},
year = {2023},
publisher = {The Eurographics Association},
ISSN = {1017-4656},
ISBN = {978-3-03868-211-0},
DOI = {10.2312/egp.20231023}
}