Content-based Image Retrieval by Indexing Random Subwindows with Randomized Trees

Raphaël Marée, Pierre Geurts, Louis Wehenkel
IPSJ Transactions on Computer Vision and Applications (open-access), Volume 1, Number 1, page 46-57 - jan 2009
Download the publication : maree-ipsj-cva-09-final.pdf [5.9Mo]  
We propose a new method for content-based image retrieval which exploits the similarity measure and indexing structure of totally randomized tree ensembles induced from a set of subwindows randomly extracted from a sample of images. We also present the possibility of updating the model as new images come in, and the capability of comparing new images using a model previously constructed from a different set of images. The approach is quantitatively evaluated on various types of images and achieves high recognition rates despite its conceptual simplicity and computational efficiency. This is an extended version of our ACCV 2007 paper.

See also

CVA is an online and open-access journal. The full paper is thus also available on publisher website IPSJ Transactions on Computer Vision and Applications, Vol. 1 (2009). Direct link.

BibTex references

@Article\{MGW09,
  author       = "Mar\'ee, Rapha{\"e}l and Geurts, Pierre and Wehenkel, Louis",
  title        = "Content-based Image Retrieval by Indexing Random Subwindows  with Randomized Trees ",
  journal      = "IPSJ Transactions on Computer Vision and Applications (open-access)",
  number       = "1",
  volume       = "1",
  pages        = "46-57",
  month        = "jan",
  year         = "2009",
  note         = "Extended version of ACCV 2007 paper.",
  url          = "http://www.montefiore.ulg.ac.be/services/stochastic/pubs/2009/MGW09"
}

Other publications in the database

» Raphaël Marée
» Pierre Geurts
» Louis Wehenkel