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Global, dense multiscale reconstruction for a billion points / Benjamin Ummenhofer in International journal of computer vision, vol 125 n° 1-3 (December 2017)  

Public [article]  inInternational journal of computer vision > vol 125 n° 1-3 (December 2017) . - pp 82 - 94 Titre : Global, dense multiscale reconstruction for a billion points Type de document : Article/Communication Auteurs : Benjamin Ummenhofer, Auteur ; Thomas Brox, Auteur Année de publication : 2017 Conférence : ICCV 2015, International Conference on Computer Vision 11/12/2015 18/12/2015 Santiago Chili OA Proceedings Article en page(s) : pp 82 - 94 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] carte de profondeur [Termes IGN] discrétisation [Termes IGN] maillage [Termes IGN] méthode des éléments finis [Termes IGN] octree [Termes IGN] reconstruction 3D [Termes IGN] reconstruction d'objet Résumé : (Auteur) We present a variational approach for surface reconstruction from a set of oriented points with scale information. We focus particularly on scenarios with nonuniform point densities due to images taken from different distances. In contrast to previous methods, we integrate the scale information in the objective and globally optimize the signed distance function of the surface on a balanced octree grid. We use a finite element discretization on the dual structure of the octree minimizing the number of variables. The tetrahedral mesh is generated efficiently with a lookup table which allows to map octree cells to the nodes of the finite elements. We optimize memory efficiency by data aggregation, such that robust data terms can be used even on very large scenes. The surface normals are explicitly optimized and used for surface extraction to improve the reconstruction at edges and corners. Numéro de notice : A2017-814 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1007/s11263-017-1017-7 En ligne : https://doi.org/10.1007/s11263-017-1017-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89256 [article]