{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T03:35:57Z","timestamp":1773200157900,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,2,23]],"date-time":"2022-02-23T00:00:00Z","timestamp":1645574400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41974213"],"award-info":[{"award-number":["41974213"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The integrity of point cloud is the basis for smoothly ensuring subsequent data processing and application. For \u201cSmart City\u201d and \u201cScan to Building Information Modeling (BIM)\u201d, complete point cloud data is essential. At present, the most commonly used methods for repairing point cloud holes are multi-source data fusion and interpolation. However, these methods either make it difficult to obtain data, or they are ineffective at repairs or labor-intensive. To solve these problems, we proposed a point cloud \u201cfuzzy\u201d repair algorithm based on the distribution regularity of buildings, aiming at the fa\u00e7ade of a building in an urban scene, especially for the vehicle Lidar point cloud. First, the point cloud was rotated to be parallel to the plane XOZ, and the feature boundaries of buildings were extracted. These boundaries were further classified as horizontal or vertical. Then, the distance between boundaries was calculated according to the Euclidean distance, and the points were divided into grids based on this distance. Finally, the holes in the grid that needed to be repaired were filled from four adjacent grids by the \u201ccopy\u2013paste\u201d method, and the final hole repairs were realized by point cloud smoothing. The quantitative results showed that data integrity improved after the repair and conformed to the state of the building. The angle and position deviation of the repaired grid were less than 0.54\u00b0 and 3.25 cm, respectively. Compared with human\u2013computer interaction and other methods, our method required less human intervention, and it had high efficiency. This is of promotional significance for the repair and modeling of point cloud in urban buildings.<\/jats:p>","DOI":"10.3390\/rs14051090","type":"journal-article","created":{"date-parts":[[2022,2,24]],"date-time":"2022-02-24T00:53:26Z","timestamp":1645664006000},"page":"1090","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["The \u201cFuzzy\u201d Repair of Urban Building Facade Point Cloud Based on Distribution Regularity"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4414-608X","authenticated-orcid":false,"given":"Zijian","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China"}]},{"given":"Xiaojun","family":"Cheng","sequence":"additional","affiliation":[{"name":"College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China"}]},{"given":"Jicang","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China"}]},{"given":"Lei","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5529-868X","authenticated-orcid":false,"given":"Yanyi","family":"Li","sequence":"additional","affiliation":[{"name":"College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China"}]},{"given":"Zhenlun","family":"Wu","sequence":"additional","affiliation":[{"name":"Big Data Development Administration of Yichun, Yichun 336000, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Yuan, L., and Bo, W. (2021). Relation-constrained 3D reconstruction of buildings in metropolitan areas from photogrammetric point clouds. Remote Sens., 13.","DOI":"10.3390\/rs13010129"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"3541","DOI":"10.1109\/TGRS.2013.2273619","article-title":"Facade reconstruction using multiview spaceborne TomoSAR point clouds","volume":"52","author":"Zhu","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.isprsjprs.2018.02.008","article-title":"Large-scale urban point cloud labeling and reconstruction","volume":"138","author":"Zhang","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1292","DOI":"10.1109\/TGRS.2015.2477429","article-title":"Automatic detection and reconstruction of 2-D\/3-D building shapes from spaceborne TomoSAR point clouds","volume":"54","author":"Shahzad","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1007\/s11263-012-0517-8","article-title":"Creating large-scale city models from 3D-point clouds: A robust approach with hybrid representation","volume":"99","author":"Lafarge","year":"2012","journal-title":"Int. J. Comput. Vis."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Mahmood, B., and Han, S. (2020). BIM-based registration and localization of 3D point clouds of indoor scenes using geometric features for augmented reality. Remote Sens., 12.","DOI":"10.3390\/rs12142302"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"793","DOI":"10.3390\/smartcities3030040","article-title":"Smart facility management: Future healthcare organization through indoor positioning systems in the light of enterprise BIM","volume":"3","author":"Tor","year":"2020","journal-title":"Smart Cities"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Ferreira, J., Resende, R., and Martinho, S. (2018). Beacons and BIM models for indoor guidance and location. Sensors, 18.","DOI":"10.20944\/preprints201810.0682.v1"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2184","DOI":"10.1016\/j.proeng.2015.09.091","article-title":"A BIM-GIS integrated web-based visualization system for low energy building design","volume":"121","author":"Niu","year":"2015","journal-title":"Procedia Eng."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.autcon.2015.04.001","article-title":"Automatic BIM component extraction from point clouds of existing buildings for sustainability applications","volume":"56","author":"Wang","year":"2015","journal-title":"Autom. Constr."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1108\/02632771311299412","article-title":"Building information modelling (BIM) for sustainable building design","volume":"31","author":"Wong","year":"2013","journal-title":"Facilities"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Ma, G., and Wu, Z. (2020). BIM-based building fire emergency management: Combining building users\u2019 behavior decisions. Autom. Constr., 109.","DOI":"10.1016\/j.autcon.2019.102975"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1109\/LGRS.2019.2916156","article-title":"Road manhole cover delineation using mobile laser scanning point cloud data","volume":"17","author":"Yu","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1016\/j.aei.2008.06.001","article-title":"An investigation into the applicability of building information models in geospatial environment in support of site selection and fire response management processes","volume":"22","author":"Isikdag","year":"2008","journal-title":"Adv. Eng. Inform."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Yi, T., Si, L., and Qian, W. (2020). Automated geometric quality inspection of prefabricated housing units using BIM and LiDAR. Remote Sens., 12.","DOI":"10.3390\/rs12152492"},{"key":"ref_16","first-page":"5627","article-title":"A survey of applications with combined BIM and 3D laser scanning in the life cycle of buildings","volume":"14","author":"Liu","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.autcon.2016.03.014","article-title":"Automated quality assessment of precast concrete elements with geometry irregularities using terrestrial laser scanning","volume":"68","author":"Wang","year":"2016","journal-title":"Autom. Constr."},{"key":"ref_18","first-page":"82","article-title":"Classification and cause analysis of terrestrial 3D laser scanning missing data","volume":"28","author":"Min","year":"2013","journal-title":"Remote Sens. Inf."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1111\/phor.12122","article-title":"Creation of parametric BIM objects from point clouds using nurbs","volume":"30","author":"Barazzetti","year":"2016","journal-title":"Photogramm. Rec."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Mart\u00edn-Lerones, P., Olmedo, D., L\u00f3pez-Vidal, A., G\u00f3mez-Garc\u00eda-Bermejo, J., and Zalama, E. (2021). BIM supported surveying and imaging combination for heritage conservation. Remote Sens., 13.","DOI":"10.3390\/rs13081584"},{"key":"ref_21","first-page":"191","article-title":"Hole filling of building fa\u00e7ade based on LIDAR point cloud","volume":"42","author":"Yong","year":"2017","journal-title":"Sci. Surv. Mapp."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1006\/cviu.2002.0963","article-title":"Geometry and texture recovery of scenes of large scale","volume":"88","author":"Stamos","year":"2002","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1023\/B:VISI.0000043756.03810.dd","article-title":"Data processing algorithms for generating textured 3D building facade meshes from laser scans and camera images","volume":"61","author":"Frueh","year":"2002","journal-title":"Int. J. Comput. Vis."},{"key":"ref_24","first-page":"27","article-title":"A method for filling absence data of airborne LIDAR point cloud","volume":"10","author":"Li","year":"2018","journal-title":"Bull. Surv. Mapp."},{"key":"ref_25","unstructured":"Kumar, A., Shih, A.M., Ito, Y., Ross, D.H., and Soni, B.K. (2007, January 14\u201317). A hole-filling algorithm using non-uniform rational B-splines. Proceedings of the 16th International Meshing Roundtable, Seattle, WA, USA."},{"key":"ref_26","first-page":"59","article-title":"Repairing holes of point cloud based on distribution regularity of building fa\u00e7ade components","volume":"34","author":"De","year":"2014","journal-title":"J. Geod. Geodyn."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Becker, S., and Haala, N. (2009, January 25\u201326). Quality dependent reconstruction of building fa\u00e7ades. Proceedings of the International Workshop on Quality of Context, Stuttgart, Germany.","DOI":"10.1007\/978-3-642-04559-2_16"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.cag.2015.03.004","article-title":"TerraMobilita\/iQmulus urban point cloud analysis benchmark","volume":"49","author":"Vallet","year":"2015","journal-title":"Comput. Graph."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Tao, L., and Xiao, C. (2018). Straight-line-segment feature-extraction method for building-fa\u00e7ade point-cloud data. Chin. J. Lasers, 46.","DOI":"10.3788\/CJL201946.1109002"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Zhe, Y., Xiao, C., Quan, L., Min, H., Jian, O., Pei, X., and Wang, G. (2017). Segmentation of point cloud in tank of plane bulkhead type. Chin. J. Lasers, 44.","DOI":"10.3788\/CJL201744.1010006"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1080\/14786440109462720","article-title":"On lines and planes of closest fit to systems of points in space","volume":"2","author":"Pearson","year":"1901","journal-title":"Lond. Edinb. Dublin Philos. Mag. J. Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1111\/j.1467-8659.2007.01016.x","article-title":"Efficient RANSAC for point-cloud shape detection","volume":"26","author":"Schnabel","year":"2010","journal-title":"Comput. Graph. Forum"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"15335","DOI":"10.1109\/TVT.2020.3040014","article-title":"Highly accurate scale estimation from multiple keyframes using RANSAC plane fitting with a novel scoring method","volume":"69","author":"Fan","year":"2020","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_34","first-page":"301","article-title":"RANSAC algorithm and elements of graph theory for automatic plane detection in 3D point clouds","volume":"24","author":"Poreba","year":"2012","journal-title":"Arch. Photogramm."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1016\/j.mechmachtheory.2015.03.004","article-title":"Euler-rodrigues formula variations, quaternion conjugation and intrinsic connections","volume":"92","author":"Dai","year":"2015","journal-title":"Mech. Mach. Theory"},{"key":"ref_36","first-page":"156","article-title":"An algorithm for terrestrial laser scanning point clouds registration based on Rodriguez matrix","volume":"37","author":"Dong","year":"2012","journal-title":"Sci. Surv. Mapp."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Rui, Z., Ming, P., Cai, L., and Yan, Z. (2019). Robust normal estimation for 3D LiDAR point clouds in urban environments. Sensors, 19.","DOI":"10.3390\/s19051248"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"De, L., Xue, L., Yang, S., and Jun, W. (2020). Deep feature-preserving normal estimation for point cloud filtering. Comput. Aided Des., 125.","DOI":"10.1016\/j.cad.2020.102860"},{"key":"ref_39","first-page":"230","article-title":"New integration approach of photogrammetric and LIDAR techniques for architectural surveys","volume":"5","author":"Fulvio","year":"2009","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/5\/1090\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:26:31Z","timestamp":1760135191000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/5\/1090"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,23]]},"references-count":39,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2022,3]]}},"alternative-id":["rs14051090"],"URL":"https:\/\/doi.org\/10.3390\/rs14051090","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,23]]}}}