{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T13:19:45Z","timestamp":1772630385536,"version":"3.50.1"},"reference-count":34,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2023,6,26]],"date-time":"2023-06-26T00:00:00Z","timestamp":1687737600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Open Access Publication Funds of Technische Universit\u00e4t Braunschweig"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper focuses on the 3D modeling of the interior spaces of buildings. Three-dimensional point clouds from laser scanners can be considered the most widely used data for 3D indoor modeling. Therefore, the walls, ceiling and floor are extracted as the main structural fabric and reconstructed. In this paper, a method is presented to tackle the problems related to the data including obstruction, clutter and noise. This method reconstructs indoor space in a model-driven approach using watertight predefined models. Employing the two-step implementation of this process, the algorithm is able to model non-rectangular spaces with an even number of sides. Afterwards, an \u201cimprovement\u201d process increases the level of details by modeling the intrusion and protrusion of the model. The 3D model is formed by extrusion from 2D to 3D. The proposed model-driven algorithm is evaluated with four benchmark real-world datasets. The efficacy of the proposed method is proved by the range of [77%, 95%], [85%, 97%] and [1.7 cm, 2.4 cm] values of completeness, correctness and geometric accuracy, respectively.<\/jats:p>","DOI":"10.3390\/s23135934","type":"journal-article","created":{"date-parts":[[2023,6,27]],"date-time":"2023-06-27T02:11:22Z","timestamp":1687831882000},"page":"5934","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Progressive Model-Driven Approach for 3D Modeling of Indoor Spaces"],"prefix":"10.3390","volume":"23","author":[{"given":"Ali","family":"Abdollahi","sequence":"first","affiliation":[{"name":"School of Engineering, Faculty of Surveying and Geospatial Engineering, University of Tehran, Tehran 1417614411, Iran"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8014-624X","authenticated-orcid":false,"given":"Hossein","family":"Arefi","sequence":"additional","affiliation":[{"name":"School of Engineering, Faculty of Surveying and Geospatial Engineering, University of Tehran, Tehran 1417614411, Iran"},{"name":"Department of Geoinformatics and Surveying, School of Engineering, Mainz University of Applied Sciences, 55128 Mainz, Germany"}]},{"given":"Shirin","family":"Malihi","sequence":"additional","affiliation":[{"name":"School of Engineering, University of Edinburgh, Edinburgh EH9 3JL, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3367-2404","authenticated-orcid":false,"given":"Mehdi","family":"Maboudi","sequence":"additional","affiliation":[{"name":"Institute of Geodesy and Photogrammetry, Technische Universit\u00e4t Braunschweig, 38106 Braunschweig, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.autcon.2014.02.021","article-title":"Productive Modeling for Development of As-Built BIM of Existing Indoor Structures","volume":"42","author":"Jung","year":"2014","journal-title":"Autom. 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