{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T02:39:13Z","timestamp":1773196753732,"version":"3.50.1"},"reference-count":63,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2018,11,7]],"date-time":"2018-11-07T00:00:00Z","timestamp":1541548800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003246","name":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","doi-asserted-by":"publisher","award":["13742"],"award-info":[{"award-number":["13742"]}],"id":[{"id":"10.13039\/501100003246","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The data acquisition with Indoor Mobile Laser Scanners (IMLS) is quick, low-cost and accurate for indoor 3D modeling. Besides a point cloud, an IMLS also provides the trajectory of the mobile scanner. We analyze this trajectory jointly with the point cloud to support the labeling of noisy, highly reflected and cluttered points in indoor scenes. An adjacency-graph-based method is presented for detecting and labeling of permanent structures, such as walls, floors, ceilings, and stairs. Through occlusion reasoning and the use of the trajectory as a set of scanner positions, gaps are discriminated from real openings in the data. Furthermore, a voxel-based method is applied for labeling of navigable space and separating them from obstacles. The results show that 80% of the doors and 85% of the rooms are correctly detected, and most of the walls and openings are reconstructed. The experimental outcomes indicate that the trajectory of MLS systems plays an essential role in the understanding of indoor scenes.<\/jats:p>","DOI":"10.3390\/rs10111754","type":"journal-article","created":{"date-parts":[[2018,11,7]],"date-time":"2018-11-07T10:32:07Z","timestamp":1541586727000},"page":"1754","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Semantic Interpretation of Mobile Laser Scanner Point Clouds in Indoor Scenes Using Trajectories"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7102-4446","authenticated-orcid":false,"given":"Shayan","family":"Nikoohemat","sequence":"first","affiliation":[{"name":"Department of Earth Observation Science, Faculty ITC, University of Twente, P.O. Box 217, 7514 AE Enschede, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9477-9905","authenticated-orcid":false,"given":"Michael","family":"Peter","sequence":"additional","affiliation":[{"name":"Independent Researcher, 46397 Bocholt, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4511-2095","authenticated-orcid":false,"given":"Sander","family":"Oude Elberink","sequence":"additional","affiliation":[{"name":"Department of Earth Observation Science, Faculty ITC, University of Twente, P.O. Box 217, 7514 AE Enschede, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8813-8028","authenticated-orcid":false,"given":"George","family":"Vosselman","sequence":"additional","affiliation":[{"name":"Department of Earth Observation Science, Faculty ITC, University of Twente, P.O. Box 217, 7514 AE Enschede, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,11,7]]},"reference":[{"key":"ref_1","unstructured":"Mozos, O.M., Stachniss, C., and Burgard, W. (2005, January 18\u201322). Supervised Learning of Places from Range Data using AdaBoost. Proceedings of the 2005 IEEE International Conference on Robotics and Automation, Barcelona, Spain."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Mozos, O.M. (2010). Semantic Labeling of Places with Mobile Robots, Springer.","DOI":"10.1007\/978-3-642-11210-2"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Ikehata, S., Yang, H., and Furukawa, Y. (2015, January 7\u201313). Structured indoor modeling. 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