{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-robust-statistics-approach-for-plane","title":"A Robust Statistics Approach for Plane Detection in Unorganized Point Clouds","arxiv_id":null,"date":"2020-04-01","proceeding":"Pattern Recognition 2020 4","authors":["Abner Matheus Costa de Araújo; Manuel Menezes de Oliveira Neto"],"abstract":"Plane detection is a key component for many applications, such as industrial reverse engineering and self-driving cars. However, existing plane-detection techniques are sensitive to noise and to user-defined parameters. We introduce a fast deterministic technique for plane detection in unorganized point clouds that is robust to noise and virtually independent of parameter tuning. It is based on a novel planarity test drawn from robust statistics and on a split and merge strategy. Its parameter values are automatically adjusted to fit the local distribution of samples in the input dataset, thus leading to good reconstruction of even small planar regions. We demonstrate the effectiveness of our solution on several real datasets, comparing its performance to state-of-art plane detection techniques, and showing that it achieves better accuracy, while still being one of the fastest.","url_abs":"https://www.sciencedirect.com/science/article/abs/pii/S0031320319304169","url_pdf":"https://www.inf.ufrgs.br/~oliveira/pubs_files/RE/Araujo_Oliveira_plane_detection_low_res.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"a-robust-statistics-approach-for-plane","repo_url":"https://github.com/abnerrjo/PlaneDetection","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"self-driving-cars","task_name":"Self-Driving Cars"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}