Aggregating local image descriptors into compact codes - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Article Dans Une Revue IEEE Transactions on Pattern Analysis and Machine Intelligence Année : 2012

Aggregating local image descriptors into compact codes

Résumé

This paper addresses the problem of large-scale image search. Three constraints have to be taken into account: search accuracy, efficiency, and memory usage. We first present and evaluate different ways of aggregating local image descriptors into a vector and show that the Fisher kernel achieves better performance than the reference bag-of-visual words approach for any given vector dimension. We then jointly optimize dimensionality reduction and indexing in order to obtain a precise vector comparison as well as a compact representation. The evaluation shows that the image representation can be reduced to a few dozen bytes while preserving high accuracy. Searching a 100 million image dataset takes about 250 ms on one processor core.
Fichier principal
Vignette du fichier
jegou_aggregate.pdf (696.72 Ko) Télécharger le fichier
Vignette du fichier
teaser.jpg (15.64 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Format : Figure, Image
Loading...

Dates et versions

inria-00633013 , version 1 (17-10-2011)

Identifiants

Citer

Hervé Jégou, Florent Perronnin, Matthijs Douze, Jorge Sánchez, Patrick Pérez, et al.. Aggregating local image descriptors into compact codes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34 (9), pp.1704-1716. ⟨10.1109/TPAMI.2011.235⟩. ⟨inria-00633013⟩
4190 Consultations
18129 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More