Coloring local feature extraction - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2006

Coloring local feature extraction

Résumé

Although color is commonly experienced as an indispensable quality in describing the world around us, state-of-the art local feature-based representations are mostly based on shape description, and ignore color information. The description of color is hampered by the large amount of variations which causes the measured color values to vary significantly. In this paper we aim to extend the description of local features with color information. To accomplish a wide applicability of the color descriptor, it should be robust to : 1. photometric changes commonly encountered in the real world, 2. varying image quality, from high quality images to snap-shot photo quality and compressed internet images. Based on these requirements we derive a set of color descriptors. The set of proposed descriptors are compared by extensive testing on multiple applications areas, namely, matching, retrieval and classification, and on a wide variety of image qualities. The results show that color descriptors remain reliable under photometric and geometrical changes, and with decreasing image quality. For all experiments a combination of color and shape outperforms a pure shape-based approach.
Fichier principal
Vignette du fichier
VS06.pdf (18.99 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

inria-00548576 , version 1 (20-12-2010)

Identifiants

Citer

Joost van de Weijer, Cordelia Schmid. Coloring local feature extraction. European Conference on Computer Vision (ECCV '06), May 2006, Graz, Austria. pp.334--348, ⟨10.1007/11744047_26⟩. ⟨inria-00548576⟩
218 Consultations
902 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More