{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:03:17Z","timestamp":1760148197568,"version":"build-2065373602"},"reference-count":44,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,4,7]],"date-time":"2023-04-07T00:00:00Z","timestamp":1680825600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["U21A20515","61972459","61971418","U2003109","62171321","62071157","62162044","LSU-KFJJ-2021-05"],"award-info":[{"award-number":["U21A20515","61972459","61971418","U2003109","62171321","62071157","62162044","LSU-KFJJ-2021-05"]}]},{"name":"Open Research Fund of Key Laboratory of Space Utilization, Chinese Academy of Sciences","award":["U21A20515","61972459","61971418","U2003109","62171321","62071157","62162044","LSU-KFJJ-2021-05"],"award-info":[{"award-number":["U21A20515","61972459","61971418","U2003109","62171321","62071157","62162044","LSU-KFJJ-2021-05"]}]},{"name":"Open Projects Program of National Laboratory of Pattern Recognition","award":["U21A20515","61972459","61971418","U2003109","62171321","62071157","62162044","LSU-KFJJ-2021-05"],"award-info":[{"award-number":["U21A20515","61972459","61971418","U2003109","62171321","62071157","62162044","LSU-KFJJ-2021-05"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Existing architecture semantic modeling methods in 3D complex urban scenes continue facing difficulties, such as limited training data, lack of semantic information, and inflexible model processing. Focusing on extracting and adopting accurate semantic information into a modeling process, this work presents a framework for lightweight modeling of buildings that joints point clouds semantic segmentation and 3D feature line detection constrained by geometric and photometric consistency. The main steps are: (1) Extraction of single buildings from point clouds using 2D-3D semi-supervised semantic segmentation under photometric and geometric constraints. (2) Generation of lightweight building models by using 3D plane-constrained multi-view feature line extraction and optimization. (3) Introduction of detailed semantics of building elements into independent 3D building models by using fine-grained segmentation of multi-view images to achieve high-accuracy architecture lightweight modeling with fine-grained semantic information. Experimental results demonstrate that it can perform independent lightweight modeling of each building on point cloud at various scales and scenes, with accurate geometric appearance details and realistic textures. It also enables independent processing and analysis of each building in the scenario, making them more useful in practical applications.<\/jats:p>","DOI":"10.3390\/rs15081957","type":"journal-article","created":{"date-parts":[[2023,4,7]],"date-time":"2023-04-07T04:04:16Z","timestamp":1680840256000},"page":"1957","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Lightweight Semantic Architecture Modeling by 3D Feature Line Detection"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4037-9900","authenticated-orcid":false,"given":"Shibiao","family":"Xu","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8600-8887","authenticated-orcid":false,"given":"Jiaxi","family":"Sun","sequence":"additional","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8212-1361","authenticated-orcid":false,"given":"Jiguang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3221-4981","authenticated-orcid":false,"given":"Weiliang","family":"Meng","sequence":"additional","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0092-6474","authenticated-orcid":false,"given":"Xiaopeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,7]]},"reference":[{"key":"ref_1","unstructured":"Qi, C.R., Su, H., Mo, K., and Guibas, L.J. 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