{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:02:26Z","timestamp":1760148146795,"version":"build-2065373602"},"reference-count":6,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2023,4,2]],"date-time":"2023-04-02T00:00:00Z","timestamp":1680393600000},"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>This Special Issue gathers papers reporting research on various aspects of the use of low-cost photogrammetric and lidar sensors for indoor building reconstruction. It includes contributions presenting improvements in the alignment of mobile mapping systems with and without a prior 3D BIM model, the interpretation of both imagery and lidar data of indoor scenery and finally the reconstruction and enrichment of existing 3D point clouds and meshes with BIM information. Concretely, the publications showcase methods and experiments for the Reconstruction of Indoor Navigation Elements for Point Cloud of Buildings with Occlusions and Openings by Wall Segment Restoration from Indoor Context Labeling, Two-Step Alignment of Mixed Reality Devices to Existing Building Data, Pose Normalization of Indoor Mapping Datasets Partially Compliant with the Manhattan World Assumption, A Robust Rigid Registration Framework of 3D Indoor Scene Point Clouds Based on RGB-D Information, 3D Point Cloud Semantic Augmentation for Instance Segmentation of 360\u00b0 Panoramas by Deep Learning Techniques and the Symmetry-Based Coarse Registration of Smartphone\u2019s Colorful Point Clouds with CAD Drawings (RegARD) for Low-Cost Digital Twin Buildings.<\/jats:p>","DOI":"10.3390\/rs15071913","type":"journal-article","created":{"date-parts":[[2023,4,3]],"date-time":"2023-04-03T02:10:13Z","timestamp":1680487813000},"page":"1913","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["3D Indoor Mapping and BIM Reconstruction Editorial"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8526-8847","authenticated-orcid":false,"given":"Maarten","family":"Bassier","sequence":"first","affiliation":[{"name":"Geomatics Research Group, Department of Civil Engineering, KU Leuven, 9000 Gent, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6368-4399","authenticated-orcid":false,"given":"Florent","family":"Poux","sequence":"additional","affiliation":[{"name":"Department of Earth Observation Science, University of Twente, 7522 NB Enschede, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7102-4446","authenticated-orcid":false,"given":"Shayan","family":"Nikoohemat","sequence":"additional","affiliation":[{"name":"Department of Earth Observation Science, University of Twente, 7522 NB Enschede, The Netherlands"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Liu, G., Wei, S., Zhong, S., Huang, S., and Zhong, R. (2022). Reconstruction of indoor navigation elements for point cloud of buildings with occlusions and openings by wall segment restoration from indoor context labeling. Remote Sens., 14.","DOI":"10.3390\/rs14174275"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Vermandere, J., Bassier, M., and Vergauwen, M. (2022). Two-step alignment of mixed reality devices to existing building data. Remote Sens., 14.","DOI":"10.3390\/rs14112680"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"H\u00fcbner, P., Weinmann, M., Wursthorn, S., and Hinz, S. (2021). Pose normalization of indoor mapping datasets partially compliant with the manhattan world assumption. Remote Sens., 13.","DOI":"10.3390\/rs13234765"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Zhong, S., Guo, M., Lv, R., Chen, J., Xie, Z., and Liu, Z. (2021). A Robust rigid registration framework of 3D indoor scene point clouds based on RGB-d information. Remote Sens., 13.","DOI":"10.3390\/rs13234755"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Karara, G., Hajji, R., and Poux, F. (2021). 3D point cloud semantic augmentation: Instance segmentation of 360\u00b0 panoramas by deep learning techniques. Remote Sens., 13.","DOI":"10.3390\/rs13183647"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Wu, Y., Shang, J., and Xue, F. (2021). RegARD: Symmetry-based coarse registration of smartphone\u2019s colorful point clouds with CAD Drawings for low-cost digital twin buildings. Remote Sens., 13.","DOI":"10.3390\/rs13101882"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/7\/1913\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:08:42Z","timestamp":1760123322000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/7\/1913"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,2]]},"references-count":6,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2023,4]]}},"alternative-id":["rs15071913"],"URL":"https:\/\/doi.org\/10.3390\/rs15071913","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2023,4,2]]}}}