Modeling Spatial Layout with Fisher Vectors for Image Categorization - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2011

Modeling Spatial Layout with Fisher Vectors for Image Categorization

Résumé

We introduce an extension of bag-of-words image representations to encode spatial layout. Using the Fisher kernel framework we derive a representation that encodes the spatial mean and the variance of image regions associated with visual words. We extend this representation by using a Gaussian mixture model to encode spatial layout, and show that this model is related to a soft-assign version of the spatial pyramid representation. We also combine our representation of spatial layout with the use of Fisher kernels to encode the appearance of local features. Through an extensive experimental evaluation, we show that our representation yields state-of-the-art image categorization results, while being more compact than spatial pyramid representations. In particular, using Fisher kernels to encode both appearance and spatial layout results in an image representation that is computationally efficient, compact, and yields excellent performance while using linear classifiers.
Fichier principal
Vignette du fichier
final.r1.pdf (374.11 Ko) Télécharger le fichier
Vignette du fichier
logo_final.png (47.29 Ko) Télécharger le fichier
Origine : Accord explicite pour ce dépôt
Format : Figure, Image
Loading...

Dates et versions

inria-00612277 , version 1 (28-07-2011)
inria-00612277 , version 2 (06-09-2011)

Identifiants

Citer

Josip Krapac, Jakob Verbeek, Frédéric Jurie. Modeling Spatial Layout with Fisher Vectors for Image Categorization. ICCV 2011 - International Conference on Computer Vision, Nov 2011, Barcelona, Spain. pp.1487-1494, ⟨10.1109/ICCV.2011.6126406⟩. ⟨inria-00612277v2⟩
1272 Consultations
3543 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More