Parameter-Free and Improved Connectivity for Point Clouds

Information

• Publication Type: Poster
• Workgroup(s)/Project(s):
  • Modeling the World at Scale
• Date: May 2023
• Publisher: Eurographics
• Open Access: yes
• Location: Saarbrücken
• ISBN: 978-3-03868-211-0
• Event: Eurographics 2023
• Editor: Singh, Gurprit and Chu, Mengyu
• DOI: 10.2312/egp.20231023
• Call for Papers: Call for Paper
• Booktitle: Eurographics 2023 - Posters
• Lecturer: Diana Marin
• Pages: 2
• Conference date: 8. May 2023 – 12. May 2023
• Pages: 5 – 6
• Keywords: Computing methodologies, Point based models

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.

Additional Files and Images

Weblinks

• Entry in reposiTUm (TU Wien Publication Database)
• DOI: 10.2312/egp.20231023

BibTeX

@misc{marin-2023-pic,
  title =      "Parameter-Free and Improved Connectivity for Point Clouds",
  author =     "Diana Marin and Stefan Ohrhallinger and Michael Wimmer",
  year =       "2023",
  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.",
  month =      may,
  publisher =  "Eurographics",
  location =   "Saarbr\"{u}cken",
  isbn =       "978-3-03868-211-0",
  event =      "Eurographics 2023",
  editor =     "Singh, Gurprit and Chu, Mengyu",
  doi =        "10.2312/egp.20231023",
  booktitle =  "Eurographics 2023 - Posters",
  pages =      "2",
  Conference date = "Poster presented at Eurographics 2023
               (2023-05-08--2023-05-12)",
  note =       "5--6",
  pages =      "5 – 6",
  keywords =   "Computing methodologies, Point based models",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2023/marin-2023-pic/",
}