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Efficient edge-aware surface mesh reconstruction for urban scenes / András Bódis-Szomorú in Computer Vision and image understanding, vol 157 (April 2017)  

Public [article]  inComputer Vision and image understanding > vol 157 (April 2017) . - pp 3 - 24 Titre : Efficient edge-aware surface mesh reconstruction for urban scenes Type de document : Article/Communication Auteurs : András Bódis-Szomorú, Auteur ; Hayko Riemenschneider, Auteur ; Luc Van Gool, Auteur Année de publication : 2017 Article en page(s) : pp 3 - 24 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] carte de profondeur [Termes IGN] données clairsemées [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] maillage par triangles [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] modèle numérique de surface [Termes IGN] reconstruction d'objet [Termes IGN] scène urbaine [Termes IGN] segmentation d'image [Termes IGN] structure-from-motion [Termes IGN] triangulation de Delaunay Résumé : (auteur) We propose an efficient approach for building compact, edge-preserving, view-centric triangle meshes from either dense or sparse depth data, with a focus on modeling architecture in large-scale urban scenes. Our method constructs a 2D base mesh from a preliminary view partitioning, then lifts the base mesh into 3D in a fast vertex depth optimization. Different view partitioning schemes are proposed for imagery and dense depth maps. They guarantee that mesh edges are aligned with crease edges and discontinuities. In particular, we introduce an effective plane merging procedure with a global error guarantee in order to maximally compact the resulting models. Moreover, different strategies for detecting and handling discontinuities are presented. We demonstrate that our approach provides an excellent trade-off between quality and compactness, and is eligible for fast production of polyhedral building models from large-scale urban height maps, as well as, for direct meshing of sparse street-side Structure-from-Motion (SfM) data. Numéro de notice : a2017-431 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.cviu.2016.06.002 En ligne : https://doi.org/10.1016/j.cviu.2016.06.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86332 [article]