A Discriminative Approach for the Retrieval of Images from Text Queries

  • David Grangier
  • Florent Monay
  • Samy Bengio
Conference paper

DOI: 10.1007/11871842_19

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4212)
Cite this paper as:
Grangier D., Monay F., Bengio S. (2006) A Discriminative Approach for the Retrieval of Images from Text Queries. In: Fürnkranz J., Scheffer T., Spiliopoulou M. (eds) Machine Learning: ECML 2006. ECML 2006. Lecture Notes in Computer Science, vol 4212. Springer, Berlin, Heidelberg

Abstract

This work proposes a new approach to the retrieval of images from text queries. Contrasting with previous work, this method relies on a discriminative model: the parameters are selected in order to minimize a loss related to the ranking performance of the model, i.e. its ability to rank the relevant pictures above the non-relevant ones when given a text query. In order to minimize this loss, we introduce an adaptation of the recently proposed Passive-Aggressive algorithm. The generalization performance of this approach is then compared with alternative models over the Corel dataset. These experiments show that our method outperforms the current state-of-the-art approaches, e.g. the average precision over Corel test data is 21.6% for our model versus 16.7% for the best alternative, Probabilistic Latent Semantic Analysis.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • David Grangier
    • 1
    • 2
  • Florent Monay
    • 1
    • 2
  • Samy Bengio
    • 1
  1. 1.IDIAP Research InstituteMartignySwitzerland
  2. 2.Ecole Polytechnique Fédérale de Lausanne (EPFL)Switzerland

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