{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T13:18:55Z","timestamp":1778246335641,"version":"3.51.4"},"reference-count":48,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2022,8,30]],"date-time":"2022-08-30T00:00:00Z","timestamp":1661817600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["72174031"],"award-info":[{"award-number":["72174031"]}]},{"name":"Beijing Key Laboratory of Operation Safety of Gas, Heating and Underground Pipelines","award":["72174031"],"award-info":[{"award-number":["72174031"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Indoor 3D reconstruction and navigation element extraction with point cloud data has become a research focus in recent years, which has important application in community refinement management, emergency rescue and evacuation, etc. Aiming at the problem that the complete wall surfaces cannot be obtained in the indoor space affected by the occluded objects and the existing methods of navigation element extraction are over-segmented or under-segmented, we propose a method to automatically reconstruct indoor navigation elements from unstructured 3D point cloud of buildings with occlusions and openings. First, the outline and occupancy information provided by the horizontal projection of the point cloud was used to guide the wall segment restoration. Second, we simulate the scanning process of a laser scanner for segmentation. Third, we use projection statistical graphs and given rules to identify missing wall surfaces and \u201chidden doors\u201d. The method is tested on several building datasets with complex structures. The results show that the method can detect and reconstruct indoor navigation elements without viewpoint information. The means of deviation in the reconstructed models is between 0\u20135 cm, and the completeness and correction are greater than 80%. However, the proposed method also has some limitations for the extraction of \u201cthick doors\u201d with a large number of occluded, non-planar components.<\/jats:p>","DOI":"10.3390\/rs14174275","type":"journal-article","created":{"date-parts":[[2022,8,31]],"date-time":"2022-08-31T00:13:56Z","timestamp":1661904836000},"page":"4275","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Reconstruction of Indoor Navigation Elements for Point Cloud of Buildings with Occlusions and Openings by Wall Segment Restoration from Indoor Context Labeling"],"prefix":"10.3390","volume":"14","author":[{"given":"Guangzu","family":"Liu","sequence":"first","affiliation":[{"name":"School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 102616, China"}]},{"given":"Shuangfeng","family":"Wei","sequence":"additional","affiliation":[{"name":"School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 102616, China"},{"name":"Engineering Research Center of Representative Building and Architectural Heritage Database, Ministry of Education, Beijing 102616, China"},{"name":"Beijing Key Laboratory of Urban Spatial Information Engineering, Beijing 102616, China"},{"name":"Beijing Key Laboratory for Architectural Heritage Fine Reconstruction and Health Monitoring, Beijing 102616, China"}]},{"given":"Shaobo","family":"Zhong","sequence":"additional","affiliation":[{"name":"Institute of Urban Systems Engineering, Beijing Academy of Science and Technology, Beijing 100035, China"}]},{"given":"Shuai","family":"Huang","sequence":"additional","affiliation":[{"name":"Beijing Digital Green Earth Technology Co., Ltd., Beijing 100085, China"}]},{"given":"Ruofei","family":"Zhong","sequence":"additional","affiliation":[{"name":"Key Laboratory of 3D Information Acquisition and Application, MOE, Capital Normal University, Beijing 100048, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"103399","DOI":"10.1016\/j.autcon.2020.103399","article-title":"Mobile indoor mapping technologies: A review","volume":"120","author":"Otero","year":"2020","journal-title":"Autom. 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