Distributed Surface Reconstruction

Information

• Publication Type: Poster
• Workgroup(s)/Project(s):
  • Modeling the World at Scale
• Date: April 2024
• Location: Limassol
• ISBN: 978-3-03868-239-4
• Event: 45th Annual Conference of the European Association for Computer Graphics (Eurographics 2024)
• Editor: Liu, Lingjie and Averkiou, Melinos
• DOI: 10.2312/egp.20241037
• Call for Papers: Call for Paper
• Booktitle: EG 2024 - Posters
• Lecturer: Diana Marin
• Pages: 2
• Conference date: 22. April 2024 – 26. April 2024
• Keywords: Surface Reconstruction, Distributed Computing, Point Clouds, High Performance Computing, delaunay triangulation

Abstract

Recent advancements in scanning technologies and their rise in availability have shifted the focus from reconstructing surfaces from point clouds of small areas to large, e.g., city-wide scenes, containing massive amounts of data. We adapt a surface reconstruction method to work in a distributed fashion on a high-performance cluster, reconstructing datasets with millions of vertices in seconds by exploiting the locality of the connectivity required by the reconstruction algorithm to efficiently divide-and-conquer the problem of creating triangulations from very large unstructured point clouds.

Additional Files and Images

Weblinks

• Entry in reposiTUm (TU Wien Publication Database)
• DOI: 10.2312/egp.20241037

BibTeX

@misc{marin-2024-dsr,
  title =      "Distributed Surface Reconstruction",
  author =     "Diana Marin and Patrick Komon and Stefan Ohrhallinger and
               Michael Wimmer",
  year =       "2024",
  abstract =   "Recent advancements in scanning technologies and their rise
               in availability have shifted the focus from reconstructing
               surfaces from point clouds of small areas to large, e.g.,
               city-wide scenes, containing massive amounts of data. We
               adapt a surface reconstruction method to work in a
               distributed fashion on a high-performance cluster,
               reconstructing datasets with millions of vertices in seconds
               by exploiting the locality of the connectivity required by
               the reconstruction algorithm to efficiently
               divide-and-conquer the problem of creating triangulations
               from very large unstructured point clouds.",
  month =      apr,
  location =   "Limassol",
  isbn =       "978-3-03868-239-4",
  event =      "45th Annual Conference of the European Association for
               Computer Graphics (Eurographics 2024)",
  editor =     "Liu, Lingjie and Averkiou, Melinos",
  doi =        "10.2312/egp.20241037",
  booktitle =  "EG 2024 - Posters",
  pages =      "2",
  Conference date = "Poster presented at 45th Annual Conference of the European
               Association for Computer Graphics (Eurographics 2024)
               (2024-04-22--2024-04-26)",
  keywords =   "Surface Reconstruction, Distributed Computing, Point Clouds,
               High Performance Computing, delaunay triangulation",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2024/marin-2024-dsr/",
}