Creating large-scale city models from 3D-point clouds: a robust approach with hybrid representation

Abstract : We present a novel and robust method for modeling cities from 3D-point data. Our algorithm pro- vides a more complete description than existing ap- proaches by reconstructing simultaneously buildings, trees and topologically complex grounds. A major con- tribution of our work is the original way of model- ing buildings which guarantees a high generalization level while having semantized and compact represen- tations. Geometric 3D-primitives such as planes, cylin- ders, spheres or cones describe regular roof sections, and are combined with mesh-patches that represent irregu- lar roof components. The various urban components in- teract through a non-convex energy minimization prob- lem in which they are propagated under arrangement constraints over a planimetric map. Our approach is ex- perimentally validated on complex buildings and large urban scenes of millions of points, and is compared to state-of-the-art methods.
Type de document :
Article dans une revue
International Journal of Computer Vision, Springer Verlag, 2012, 99 (1), pp.69-85
Liste complète des métadonnées

Littérature citée [46 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-00759265
Contributeur : Florent Lafarge <>
Soumis le : vendredi 30 novembre 2012 - 12:50:10
Dernière modification le : jeudi 11 janvier 2018 - 16:17:44
Document(s) archivé(s) le : vendredi 1 mars 2013 - 03:51:21

Fichier

ijcv_2012.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-00759265, version 1

Collections

Citation

Florent Lafarge, Clément Mallet. Creating large-scale city models from 3D-point clouds: a robust approach with hybrid representation. International Journal of Computer Vision, Springer Verlag, 2012, 99 (1), pp.69-85. 〈hal-00759265〉

Partager

Métriques

Consultations de la notice

235

Téléchargements de fichiers

3027