{"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/robust-large-scale-localization-in-3d-point","title":"Robust Large-Scale Localization in 3D Point Clouds Revisited","arxiv_id":"1511.01156","date":"2015-11-03","proceeding":null,"authors":["Fabian Tschopp","Marco Zorzi"],"abstract":"We tackle the problem of getting a full 6-DOF pose estimation of a query\nimage inside a given point cloud. This technical report re-evaluates the\nalgorithms proposed by Y. Li et al. \"Worldwide Pose Estimation using 3D Point\nCloud\". Our code computes poses from 3 or 4 points, with both known and unknown\nfocal length. The results can easily be displayed and analyzed with Meshlab. We\nfound both advantages and shortcomings of the methods proposed. Furthermore,\nadditional priors and parameters for point selection, RANSAC and pose quality\nestimate (inlier test) are proposed and applied.","url_abs":"http://arxiv.org/abs/1511.01156v1","url_pdf":"http://arxiv.org/pdf/1511.01156v1.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":"robust-large-scale-localization-in-3d-point","repo_url":"https://github.com/naibaf7/pose_estimation","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"pose-estimation","task_name":"Pose Estimation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}