An A Contrario Model for Matching Interest Points under Geometric and Photometric Constraints

Frédéric Sur 1 Nicolas Noury 2 Marie-Odile Berger 1
1 MAGRIT - Visual Augmentation of Complex Environments
Inria Nancy - Grand Est, LORIA - ALGO - Department of Algorithms, Computation, Image and Geometry
2 MAGRIT - Visual Augmentation of Complex Environments
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Finding point correspondences between two views is generally based on the matching of local photometric descriptors. A subsequent geometric constraint ensures that the set of matching points is consistent with a realistic camera motion. Starting from a paper by Moisan and Stival, we propose an a contrario model for matching interest points based on descriptor similarity and geometric constraints. The resulting algorithm has adaptive matching thresholds and is able to detect point correspondences whose associated descriptors are not the first nearest neighbor. We also discuss the specific difficulties raised by images containing repeated patterns which are likely to introduce correspondences beyond the nearest neighbor.
Liste complète des métadonnées

Littérature citée [25 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-00876215
Contributeur : Frédéric Sur <>
Soumis le : jeudi 24 octobre 2013 - 10:05:54
Dernière modification le : lundi 3 décembre 2018 - 15:46:13
Document(s) archivé(s) le : lundi 27 janvier 2014 - 12:15:10

Fichier

120871766.pdf
Fichiers éditeurs autorisés sur une archive ouverte

Identifiants

Collections

Citation

Frédéric Sur, Nicolas Noury, Marie-Odile Berger. An A Contrario Model for Matching Interest Points under Geometric and Photometric Constraints. SIAM Journal on Imaging Sciences, Society for Industrial and Applied Mathematics, 2013, 6 (4), pp.1956-1978. 〈http://epubs.siam.org/doi/abs/10.1137/120871766〉. 〈10.1137/120871766〉. 〈hal-00876215〉

Partager

Métriques

Consultations de la notice

475

Téléchargements de fichiers

234