{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T16:36:40Z","timestamp":1773247000721,"version":"3.50.1"},"reference-count":37,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2021,6,4]],"date-time":"2021-06-04T00:00:00Z","timestamp":1622764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key Science and Technology Project of Ministry of Transport of China","award":["2020-MS5-147"],"award-info":[{"award-number":["2020-MS5-147"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No. 42071437, 41631174"],"award-info":[{"award-number":["No. 42071437, 41631174"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Sichuan Science and Technology Program","award":["No. 2020YFG0083"],"award-info":[{"award-number":["No. 2020YFG0083"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Today, mobile laser scanning and oblique photogrammetry are two standard urban remote sensing acquisition methods, and the cross-source point-cloud data obtained using these methods have significant differences and complementarity. Accurate co-registration can make up for the limitations of a single data source, but many existing registration methods face critical challenges. Therefore, in this paper, we propose a systematic incremental registration method that can successfully register MLS and photogrammetric point clouds in the presence of a large number of missing data, large variations in point density, and scale differences. The robustness of this method is due to its elimination of noise in the extracted linear features and its 2D incremental registration strategy. There are three main contributions of our work: (1) the development of an end-to-end automatic cross-source point-cloud registration method; (2) a way to effectively extract the linear feature and restore the scale; and (3) an incremental registration strategy that simplifies the complex registration process. The experimental results show that this method can successfully achieve cross-source data registration, while other methods have difficulty obtaining satisfactory registration results efficiently. Moreover, this method can be extended to more point-cloud sources.<\/jats:p>","DOI":"10.3390\/rs13112195","type":"journal-article","created":{"date-parts":[[2021,6,7]],"date-time":"2021-06-07T01:56:40Z","timestamp":1623031000000},"page":"2195","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Linear-Based Incremental Co-Registration of MLS and Photogrammetric Point Clouds"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9406-0535","authenticated-orcid":false,"given":"Shiming","family":"Li","sequence":"first","affiliation":[{"name":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuming","family":"Ge","sequence":"additional","affiliation":[{"name":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shengfu","family":"Li","sequence":"additional","affiliation":[{"name":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China"},{"name":"Sichuan Highway Planning, Survey, Design and Research Institute Ltd., Chengdu 610000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Xu","sequence":"additional","affiliation":[{"name":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhendong","family":"Wang","sequence":"additional","affiliation":[{"name":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3349","DOI":"10.1109\/JSTARS.2018.2856900","article-title":"A Volumetric Fusing Method for TLS and SFM Point Clouds","volume":"11","author":"Li","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2427","DOI":"10.1080\/01431161.2016.1252477","article-title":"Forestry applications of UAVs in Europe: A review","volume":"38","author":"Torresan","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.isprsjprs.2018.03.004","article-title":"Integration of aerial oblique imagery and terrestrial imagery for optimized 3D modeling in urban areas","volume":"139","author":"Wu","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.isprsjprs.2015.01.002","article-title":"Flexible building primitives for 3D building modeling","volume":"101","author":"Xiong","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1111\/cgf.12802","article-title":"A Survey of Surface Reconstruction from Point Clouds","volume":"36","author":"Berger","year":"2016","journal-title":"Comput. Graph. Forum"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/19479832.2016.1160960","article-title":"Advances in fusion of optical imagery and LiDAR point cloud applied to photogrammetry and remote sensing","volume":"8","author":"Zhang","year":"2016","journal-title":"Int. J. Image Data Fusion"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Xie, L., Zhu, Q., Hu, H., Wu, B., Li, Y., Zhang, Y., and Zhong, R. (2018). Hierarchical Regularization of Building Boundaries in Noisy Aerial Laser Scanning and Photogrammetric Point Clouds. Remote Sens., 10.","DOI":"10.3390\/rs10121996"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1016\/j.isprsjprs.2017.06.011","article-title":"Automatic markerless registration of point clouds with semantic-keypoint-based 4-points congruent sets","volume":"130","author":"Ge","year":"2017","journal-title":"ISPRS J. Photogramm."},{"key":"ref_9","unstructured":"Habib, A., De Tchev, I., and Bang, K. (2010, January 15\u201318). A Comparative Analysis of Two Approaches for Multiple-Surface Registration of Irregular Point Clouds. Proceedings of the 2010 Canadian Geomatics Conference and Symposium of Commission I, ISPRS Convergence in Geomatics\u2014Shaping Canada\u2019s Competitive Landscape, Calgary, AB, Canada."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.isprsjprs.2017.10.001","article-title":"Pairwise Registration of TLS Point Clouds using Covariance Descriptors and a Non-cooperative Game","volume":"134","author":"Zai","year":"2017","journal-title":"ISPRS J. Photogramm."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"437","DOI":"10.5194\/isprs-archives-XLII-1-437-2018","article-title":"Combining Airborne Oblique Camera and Lidar Sensors: Investigation and New Perspectives","volume":"XLII-1","author":"Toschi","year":"2018","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/S0924-2716(98)00013-6","article-title":"Errors and accuracy estimates of laser data acquired by various laser scanning systems for topographic applications","volume":"53","author":"Huising","year":"1998","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Yan, L., Tan, J., and Liu, H. (2017). Automatic Registration of TLS-TLS and TLS-MLS Point Clouds Using a Genetic Algorithm. Sensors, 17.","DOI":"10.3390\/s17091979"},{"key":"ref_14","first-page":"239","article-title":"A Method for Registration of 3-D Shapes","volume":"14","author":"Besl","year":"1992","journal-title":"Proc. Spie Int. Soc. Opt. Eng."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/0262-8856(92)90066-C","article-title":"Object modelling by registration of multiple range images","volume":"10","author":"Chen","year":"1992","journal-title":"Image Vis. Comput."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Censi, A. (2008, January 19\u201323). An ICP variant using a point-to-line metric. Proceedings of the IEEE International Conference on Robotics and Automation, Pasadena, CA, USA.","DOI":"10.1109\/ROBOT.2008.4543181"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Koide, K., Yokozuka, M., Oishi, S., and Banno, A. (June, January 30). Voxelized GICP for Fast and Accurate 3D Point Cloud Registration. Proceedings of the 2021 IEEE International Conference on Robotics and Automation, Xi\u2019an, China.","DOI":"10.1109\/ICRA48506.2021.9560835"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Cheng, L., Chen, S., Liu, X., Xu, H., Wu, Y., Li, M., and Chen, Y. (2018). Registration of Laser Scanning Point Clouds: A Review. Sensors, 18.","DOI":"10.3390\/s18051641"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"35","DOI":"10.5194\/isprs-archives-XLII-1-W1-35-2017","article-title":"Hierarchical Regularization of Polygons for Photogrammetric Point Clouds of Oblique Images","volume":"XLII-1\/W1","author":"Xie","year":"2017","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_20","unstructured":"Stamos, I., and Leordeanu, M. (2003, January 18\u201320). Automated Feature-Based Range Registration of Urban Scenes of Large Scale. Proceedings of the IEEE Internal Conference of Computer Vision & Pattern Recognition, Madison, WI, USA."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.isprsjprs.2015.08.006","article-title":"An automated method to register airborne and terrestrial laser scanning point clouds","volume":"109","author":"Yang","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.isprsjprs.2014.10.005","article-title":"Hierarchical extraction of urban objects from mobile laser scanning data","volume":"99","author":"Yang","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"769","DOI":"10.1109\/TGRS.2020.2995574","article-title":"Multientity Registration of Point Clouds for Dynamic Objects on Complex Floating Platform Using Object Silhouettes","volume":"59","author":"Wang","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.isprsjprs.2014.05.012","article-title":"Automated registration of dense terrestrial laser-scanning point clouds using curves","volume":"95","author":"Yang","year":"2014","journal-title":"ISPRS J. Photogramm."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1109\/JSTARS.2017.2752765","article-title":"A Symmetry-Based Method for LiDAR Point Registration","volume":"11","author":"Cheng","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1016\/j.isprsjprs.2006.09.006","article-title":"An integrated approach for modelling and global registration of point clouds \u2014ScienceDirect","volume":"61","author":"Rabbani","year":"2007","journal-title":"ISPRS J. Photogramm."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Zang, Y., Yang, B., Li, J., and Guan, H. (2019). An Accurate TLS and UAV Image Point Clouds Registration Method for Deformation Detection of Chaotic Hillside Areas. Remote Sens., 11.","DOI":"10.3390\/rs11060647"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.isprsjprs.2018.11.016","article-title":"Practical optimal registration of terrestrial LiDAR scan pairs","volume":"147","author":"Cai","year":"2019","journal-title":"ISPRS J. Photogramm."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Fan, B., Wu, F., and Hu, Z. (2010, January 13\u201318). Line Matching Leveraged by Point Correspondences. Proceedings of the 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA.","DOI":"10.1109\/CVPR.2010.5540186"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1016\/j.isprsjprs.2017.03.010","article-title":"Contextual segment-based classification of airborne laser scanner data","volume":"128","author":"Vosselman","year":"2017","journal-title":"ISPRS J. Photogramm."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1080\/02664763.2015.1070806","article-title":"Identification and classification of multiple outliers, high leverage points and influential observations in linear regression","volume":"43","author":"Nurunnabi","year":"2016","journal-title":"J. Appl. Stats"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1023\/A:1009769707641","article-title":"Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values","volume":"2","author":"Huang","year":"1998","journal-title":"Data Min. Knowl. Disc."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1109\/TPAMI.2008.300","article-title":"LSD: A Fast Line Segment Detector with a False Detection Control","volume":"32","author":"Gioi","year":"2010","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_34","unstructured":"Lu, W., Neumann, U., and You, S. (October, January 29). Wide-Baseline Image Matching using Line Signatures. Proceedings of the 2009 IEEE 12th International Conference on Computer Vision, Kyoto, Japan."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1109\/TPAMI.2007.1144","article-title":"Groups of Adjacent Contour Segments for Object Detection","volume":"30","author":"Ferrari","year":"2007","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1016\/j.isprsjprs.2020.01.020","article-title":"Object-based incremental registration of terrestrial point clouds in an urban environment","volume":"161","author":"Ge","year":"2020","journal-title":"ISPRS J. Photogramm."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.isprsjprs.2018.06.018","article-title":"Hierarchical registration of unordered TLS point clouds based on binary shape context descriptor","volume":"144","author":"Dong","year":"2018","journal-title":"ISPRS J. Photogramm."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/11\/2195\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:10:56Z","timestamp":1760163056000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/11\/2195"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,4]]},"references-count":37,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2021,6]]}},"alternative-id":["rs13112195"],"URL":"https:\/\/doi.org\/10.3390\/rs13112195","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,6,4]]}}}