{"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/automatic-extrinsic-calibration-between-a","title":"Automatic extrinsic calibration between a camera and a 3D Lidar using 3D point and plane correspondences","arxiv_id":"1904.12433","date":"2019-04-29","proceeding":null,"authors":["Surabhi Verma","Julie Stephany Berrio","Stewart Worrall","Eduardo Nebot"],"abstract":"This paper proposes an automated method to obtain the extrinsic calibration\nparameters between a camera and a 3D lidar with as low as 16 beams. We use a\ncheckerboard as a reference to obtain features of interest in both sensor\nframes. The calibration board centre point and normal vector are automatically\nextracted from the lidar point cloud by exploiting the geometry of the board.\nThe corresponding features in the camera image are obtained from the camera's\nextrinsic matrix. We explain the reasons behind selecting these features, and\nwhy they are more robust compared to other possibilities. To obtain the optimal\nextrinsic parameters, we choose a genetic algorithm to address the highly\nnon-linear state space. The process is automated after defining the bounds of\nthe 3D experimental region relative to the lidar, and the true board\ndimensions. In addition, the camera is assumed to be intrinsically calibrated.\nOur method requires a minimum of 3 checkerboard poses, and the calibration\naccuracy is demonstrated by evaluating our algorithm using real world and\nsimulated features.","url_abs":"http://arxiv.org/abs/1904.12433v1","url_pdf":"http://arxiv.org/pdf/1904.12433v1.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":"automatic-extrinsic-calibration-between-a","repo_url":"https://github.com/chinitaberrio/cam_lidar_calibration","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"automatic-extrinsic-calibration-between-a","repo_url":"https://github.com/acfr/cam_lidar_calibration","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1904.12433","atlas_url":"https://app.syntology.ai/?focus=1904.12433","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}