Correlation-Based Burstiness for Logo Retrieval - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2012

Correlation-Based Burstiness for Logo Retrieval

Résumé

Detecting logos in photos is challenging. A reason is that logos locally resemble patterns frequently seen in random images. We propose to learn a statistical model for the distribution of incorrect detections output by an image matching algorithm. It results in a novel scoring criterion in which the weight of correlated keypoint matches is reduced, penalizing irrelevant logo detections. In experiments on two very diff erent logo retrieval benchmarks, our approach largely improves over the standard matching criterion as well as other state-of-the-art approaches.
Fichier principal
Vignette du fichier
msp073-revaud.pdf (1.11 Mo) Télécharger le fichier
Vignette du fichier
thumbs.jpg (34.93 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Format : Figure, Image
Loading...

Dates et versions

hal-00728502 , version 1 (06-09-2012)

Identifiants

Citer

Jérôme Revaud, Matthijs Douze, Cordelia Schmid. Correlation-Based Burstiness for Logo Retrieval. MM 2012 - ACM International Conference on Multimedia, Oct 2012, Nara, Japan. pp.965-968, ⟨10.1145/2393347.2396358⟩. ⟨hal-00728502⟩
560 Consultations
1289 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More