What Makes Paris Look Like Paris?

Carl Doersch 1 Saurabh Singh 1 Abhinav Gupta 1 Josef Sivic 2, 3 Alexei Efros 4
3 WILLOW - Models of visual object recognition and scene understanding
DI-ENS - Département d'informatique de l'École normale supérieure, ENS Paris - École normale supérieure - Paris, Inria Paris-Rocquencourt, CNRS - Centre National de la Recherche Scientifique : UMR8548
Abstract : Given a large repository of geo-tagged imagery, we seek to automatically find visual elements, for example windows, balconies, and street signs, that are most distinctive for a certain geo-spatial area, for example the city of Paris. This is a tremendously difficult task as the visual features distinguishing architectural elements of different places can be very subtle. In addition, we face a hard search problem: given all possible patches in all images, which of them are both frequently occurring and geographically informative? To address these issues, we propose to use a discriminative clustering approach able to take into account the weak geographic supervision. We show that geographically representative image elements can be discovered automatically from Google Street View imagery in a discriminative manner. We demonstrate that these elements are visually interpretable and perceptually geo-informative. The discovered visual elements can also support a variety of computational geography tasks, such as mapping architectural correspondences and influences within and across cities, finding representative elements at different geo-spatial scales, and geographically informed image retrieval.
Type de document :
Article dans une revue
Communications of the ACM, ACM, 2015, 58 (12), pp.103-110. 〈10.1145/2830541〉
Liste complète des métadonnées

Littérature citée [22 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01248528
Contributeur : Josef Sivic <>
Soumis le : jeudi 31 décembre 2015 - 00:16:00
Dernière modification le : jeudi 11 janvier 2018 - 06:23:05
Document(s) archivé(s) le : mardi 5 avril 2016 - 09:47:23

Fichier

Doersch15author.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

Citation

Carl Doersch, Saurabh Singh, Abhinav Gupta, Josef Sivic, Alexei Efros. What Makes Paris Look Like Paris?. Communications of the ACM, ACM, 2015, 58 (12), pp.103-110. 〈10.1145/2830541〉. 〈hal-01248528〉

Partager

Métriques

Consultations de la notice

214

Téléchargements de fichiers

232