SIGnificant Outlier Removal

Information

• Publication Type: Conference Paper
• Workgroup(s)/Project(s):
  • Modeling the World at Scale
• Date: February 2026
• ISBN: 978-3-032-07623-6
• Publisher: Springer
• Open Access: yes
• Location: Rome
• Lecturer: Diana Marin
• Event: 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2024)
• Editor: Bashford-Rogers, Thomas and Meneveaux, Daniel and Ziat, Mounia and Ammi, Mehdi and Jänicke, Stefan and Purchase, Helen and Radeva, Petia and Furnari, Antonino and Bouatouch, Kadi and de Sousa, A. Augusto
• DOI: 10.1007/978-3-032-07623-6_4
• Booktitle: Computer Vision, Imaging and Computer Graphics Theory and Applications : 19th International Joint Conference, VISIGRAPP 2024, Rome, Italy, February 27–29, 2024, Revised Selected Papers
• Pages: 14
• Volume: 2548
• Conference date: 27. February 2024 – 29. February 2024
• Pages: 67 – 80
• Keywords: Outlier removal, Point clouds, Proximity graphs

Abstract

Point clouds, usually obtained through scanning or various image processing, are commonly affected by noise and outliers. Such artifacts compromise data quality as they significantly distort subsequent processes, such as normal estimation and surface reconstruction. In this work, we introduce a proximity-based outlier removal method for point clouds. We improve on statistical methods based on neighboring graphs by using a parameter-free proximity graph—the spheres-of-influence (SIG), thus requiring fewer parameters compared to classical methods and obtaining better results. Moreover, the simplicity of our method allows it to become an easy replacement for existing statistical methods.

Additional Files and Images

Weblinks

• Entry in reposiTUm (TU Wien Publication Database)
• DOI: 10.1007/978-3-032-07623-6_4

BibTeX

@inproceedings{marin-2026-sor,
  title =      "SIGnificant Outlier Removal",
  author =     "Diana Marin and Filip Ilic and Stefan Ohrhallinger and
               Michael Wimmer",
  year =       "2026",
  abstract =   "Point clouds, usually obtained through scanning or various
               image processing, are commonly affected by noise and
               outliers. Such artifacts compromise data quality as they
               significantly distort subsequent processes, such as normal
               estimation and surface reconstruction. In this work, we
               introduce a proximity-based outlier removal method for point
               clouds. We improve on statistical methods based on
               neighboring graphs by using a parameter-free proximity
               graph—the spheres-of-influence (SIG), thus requiring fewer
               parameters compared to classical methods and obtaining
               better results. Moreover, the simplicity of our method
               allows it to become an easy replacement for existing
               statistical methods.",
  month =      feb,
  isbn =       "978-3-032-07623-6",
  publisher =  "Springer",
  location =   "Rome",
  event =      "19th International Joint Conference on Computer Vision,
               Imaging and Computer Graphics Theory and Applications
               (VISIGRAPP 2024)",
  editor =     "Bashford-Rogers, Thomas and Meneveaux, Daniel and Ziat,
               Mounia and Ammi, Mehdi and J\"{a}nicke, Stefan and Purchase,
               Helen and Radeva, Petia and Furnari, Antonino and Bouatouch,
               Kadi and de Sousa, A. Augusto",
  doi =        "10.1007/978-3-032-07623-6_4",
  booktitle =  "Computer Vision, Imaging and Computer Graphics Theory and
               Applications : 19th International Joint Conference,
               VISIGRAPP 2024, Rome, Italy, February 27–29, 2024, Revised
               Selected Papers",
  pages =      "14",
  volume =     "2548",
  pages =      "67--80",
  keywords =   "Outlier removal, Point clouds, Proximity graphs",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2026/marin-2026-sor/",
}