{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T16:56:42Z","timestamp":1775667402306,"version":"3.50.1"},"reference-count":65,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2020,6,14]],"date-time":"2020-06-14T00:00:00Z","timestamp":1592092800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The integration of the camera and LiDAR has played an important role in the field of autonomous driving, for example in visual\u2013LiDAR SLAM and 3D environment fusion perception, which rely on precise geometrical extrinsic calibration. In this paper, we proposed a fully automatic end-to-end method based on the 3D\u20132D corresponding mask (CoMask) to directly estimate the extrinsic parameters with high precision. Simple subtraction was applied to extract the candidate point cluster from the complex background, and then 3D LiDAR points located on checkerboard were selected and refined by spatial growth clustering. Once the distance transform of 2D checkerboard mask was generated, the extrinsic calibration of the two sensors could be converted to 3D\u20132D mask correspondence alignment. A simple but efficient strategy combining the genetic algorithm with the Levenberg\u2013Marquardt method was used to solve the optimization problem globally without any initial estimates. Both simulated and realistic experiments showed that the proposed method could obtain accurate results without manual intervention, special environment setups, or prior initial parameters. Compared with the state of the art, our method has obvious advantages in accuracy, robustness, and noise resistance. Our code is open-source on GitHub.<\/jats:p>","DOI":"10.3390\/rs12121925","type":"journal-article","created":{"date-parts":[[2020,6,15]],"date-time":"2020-06-15T05:56:27Z","timestamp":1592200587000},"page":"1925","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["CoMask: Corresponding Mask-Based End-to-End Extrinsic Calibration of the Camera and LiDAR"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4445-7152","authenticated-orcid":false,"given":"Lu","family":"Yin","sequence":"first","affiliation":[{"name":"State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bin","family":"Luo","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0172-1582","authenticated-orcid":false,"given":"Wei","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huan","family":"Yu","sequence":"additional","affiliation":[{"name":"Wuhan InDriving Technology Co., Ltd., Innovation Building 1802, Hongshan District, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenjie","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4422-6584","authenticated-orcid":false,"given":"Chengyuan","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,14]]},"reference":[{"key":"ref_1","unstructured":"Cui, Y., Chen, R., Chu, W., Chen, L., Tian, D., and Cao, D. 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