Building recognition with adaptive interest point selection

Abstract : In this paper, we propose an improvement of image retrieval for building images using the Bag of Words (BoW) model. The principle consists of pre-processing the interest points detected on the images in order to classify them into two classes, corresponding to building and no-building key points. In this way, the data involved for comparisons is reduced to only the relevant one and only the features describing the buildings are taken into account. The experimental results, carried out on the Paris6k data set shows significant improvement in terms of retrieval performances
Type de document :
Communication dans un congrès
ICCE 2017 : International Conference on Consumer Electronics, Jan 2017, Las Vegas United States. IEEE Computer Society, Proceedings ICCE 2017 : International Conference on Consumer Electronics, pp.1 - 4, 2017, 〈10.1109/ICCE.2017.7889218〉
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01511886
Contributeur : Médiathèque Télécom Sudparis & Institut Mines-Télécom Business School <>
Soumis le : vendredi 21 avril 2017 - 17:11:06
Dernière modification le : jeudi 31 mai 2018 - 09:12:02

Identifiants

Citation

Nicolas Hascoet, Titus Zaharia. Building recognition with adaptive interest point selection. ICCE 2017 : International Conference on Consumer Electronics, Jan 2017, Las Vegas United States. IEEE Computer Society, Proceedings ICCE 2017 : International Conference on Consumer Electronics, pp.1 - 4, 2017, 〈10.1109/ICCE.2017.7889218〉. 〈hal-01511886〉

Partager

Métriques

Consultations de la notice

60