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Chapitre D'ouvrage Année : 2010

Multimodal Image Retrieval over a Large Database

Résumé

We introduce a new multimodal retrieval technique which combines query reformulation and visual image reranking in order to deal with results sparsity and imprecision, respectively. Textual queries are reformulated using Wikipedia knowledge and results are then reordered using a k-NN based reranking method. We compare textual and multimodal retrieval and show that introducing visual reranking results in a significant improvement of performance.
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Dates et versions

hal-00933265 , version 1 (20-01-2014)

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  • HAL Id : hal-00933265 , version 1

Citer

Débora Mayupo, Adrian Popescu, Hervé Le Borgne, Pierre-Alain Moellic. Multimodal Image Retrieval over a Large Database. Multilingual Information Access Evaluation II. Multimedia Experiments : 10th Workshop of the Cross-Language Evaluation Forum, CLEF 2009, Corfu, Greece, September 30 - October 2, 2009, Revised Selected Papers, Springer, pp.177-184, 2010, Lecture Notes in Computer Science. ⟨hal-00933265⟩
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