A Discriminative Approach for the Retrieval of Images from Text Queries
| Type of publication: | Conference paper |
| Citation: | grangier:2006:ecml |
| Booktitle: | European Conference on Machine Learning (ECML) |
| Year: | 2006 |
| 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. |
| Userfields: | ipdmembership={Learning}, ipdxref={techreport:grangier_rr06-15.bib}, |
| Keywords: | |
| Projects: |
Idiap |
| Authors: | |
| Added by: | [UNK] |
| Total mark: | 0 |
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