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Communication Dans Un Congrès Année : 2011

Efficient bag-of-feature kernel representation for image similarity search

Résumé

Although “Bag-of-Features” image models have shown very good potential for object matching and image retrieval, such a complex data representation requires computationally expensive similarity measure evaluation. In this paper, we propose a framework unifying dictionary-based and kernel-based similarity functions that highlights the tradeoff between powerful data representation and eff cient similarity computation. On the basis of this formalism, we propose a new kernel-based similarity approach for Bag-of-Feature descriptions. We introduce a method for fast similarity search in large image databases. The conducted experiments prove that our approach is very competitive among State-of-the-art methods for similarity retrieval tasks.
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Dates et versions

hal-00773095 , version 1 (11-01-2013)

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Frédéric Precioso, Matthieu Cord, David Gorisse, Nicolas Thome. Efficient bag-of-feature kernel representation for image similarity search. ICIP 2011 - IEEE International Conference on Image Processing, Sep 2011, Bruxelles, Belgium. pp.109-112, ⟨10.1109/ICIP.2011.6115618⟩. ⟨hal-00773095⟩
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