Hamming Embedding Similarity-based Image Classification - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2012

Hamming Embedding Similarity-based Image Classification

Mihir Jain
  • Function : Author
  • PersonId : 905230
Rachid Benmokhtar
  • Function : Author
  • PersonId : 923924
Patrick Gros
Hervé Jégou
  • Function : Author
  • PersonId : 833473


In this paper, we have presented a novel approach to image classification based on a matching technique. It consists in combining the Hamming-Embedding similarity-based matching method with a similarity space encoding, which subsequently allows the use of a linear SVM. This method is efficient and achieves state-of-the-art classification results on two reference image classification benchmarks: the PASCAL VOC 2007 and Caltech-256 datasets. Moreover, it is shown to be complementary with the other best classification method based, namely the Fisher kernel. To our knowledge, this method is the first matching-based approach to provide such competitive results. We believe that the flexibility offered by this framework is likely to be extended, in particular for a better integration of the geometrical constraints. As a secondary contribution, we have proposed an effective variant of the SIFT descriptor, which gives a slight yet consistent improvement on classification accuracy. Its interest has been validated with the Fisher Kernel.
Fichier principal
Vignette du fichier
hal_v1.pdf (345.32 Ko) Télécharger le fichier
Vignette du fichier
he_classif.png (47.55 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Format : Figure, Image

Dates and versions

hal-00688169 , version 1 (16-04-2012)


  • HAL Id : hal-00688169 , version 1


Mihir Jain, Rachid Benmokhtar, Patrick Gros, Hervé Jégou. Hamming Embedding Similarity-based Image Classification. ICMR - ACM International Conference on Multimedia Retrieval, Jun 2012, Hong-Kong, Hong Kong SAR China. ⟨hal-00688169⟩
828 View
1668 Download


Gmail Facebook X LinkedIn More