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Generation of concise 3D building model from dense meshes by extracting and completing planar primitives / Xinyi Liu in Photogrammetric record, vol 38 n° 181 (March 2023)  

Public [article]  inPhotogrammetric record > vol 38 n° 181 (March 2023) . - pp 22 - 46 Titre : Generation of concise 3D building model from dense meshes by extracting and completing planar primitives Type de document : Article/Communication Auteurs : Xinyi Liu, Auteur ; Xianzhang Zhu, Auteur ; Yongjun Zhang, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 22 - 46 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie [Termes IGN] adjacence [Termes IGN] bati [Termes IGN] maillage [Termes IGN] modélisation 3D du bâti BIM [Termes IGN] modélisation du bâti [Termes IGN] primitive géométrique [Termes IGN] reconstruction 3D [Termes IGN] segmentation en plan [Termes IGN] semis de points Résumé : (auteur) The generation of a concise building model has been and continues to be a challenge in photogrammetry and computer graphics. The current methods typically focus on the simplicity and fidelity of the model, but those methods either fail to preserve the structural information or suffer from low computational efficiency. In this paper, we propose a novel method to generate concise building models from dense meshes by extracting and completing the planar primitives of the building. From the perspective of probability, we first extract planar primitives from the input mesh and obtain the adjacency relationships between the primitives. Since primitive loss and structural defects are inevitable in practice, we employ a novel structural completion approach to eliminate linkage errors. Finally, the concise polygonal mesh is reconstructed by connectivity-based primitive assembling. Our method is efficient and robust to various challenging data. Experiments on various building models revealed the efficacy and applicability of our method. Numéro de notice : A2023-162 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12438 Date de publication en ligne : 04/01/2023 En ligne : https://doi.org/10.1111/phor.12438 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102865 [article]