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
} }
Citation