Communication Dans Un Congrès Année : 2008

Learning Distance Functions for Automatic Annotation of Images

Résumé

This paper gives an overview of recent approaches towards image representation and image similarity computation for content-based image retrieval and automatic image annotation (category tagging). Additionaly, a new similarity function between an image and an object class is proposed. This similarity function combines various aspects of object class appearance through use of representative images of the class. Similarity to a representative image is determined by weighting local image similarities, where weights are learned from training image pairs, labeled "same" and "different", using linear SVM. The proposed approach is validated on a challenging dataset where it performed favorably.

Fichier principal
Vignette du fichier
kj07amr.pdf (2.38 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Licence
Loading...

Dates et versions

inria-00548684 , version 1 (25-01-2011)

Licence

Identifiants

Citer

Josip Krapac, Frédéric Jurie. Learning Distance Functions for Automatic Annotation of Images. AMR - 5th International Workshop on Adaptive Multimedia Retrieval, Jul 2007, Paris, France. pp.1-16, ⟨10.1007/978-3-540-79860-6_1⟩. ⟨inria-00548684⟩
438 Consultations
473 Téléchargements

Altmetric

Partager

  • More