Bio-Inspired Bags-of-Features for Image Classification

Wafa Bel Haj Ali 1 Eric Debreuve 1 Pierre Kornprobst 2 Michel Barlaud 1
2 NEUROMATHCOMP
CRISAM - Inria Sophia Antipolis - Méditerranée , INRIA Rocquencourt, ENS Paris - École normale supérieure - Paris, UNS - Université Nice Sophia Antipolis, CNRS - Centre National de la Recherche Scientifique : UMR8548
Abstract : The challenge of image classification is based on two key elements: the image representation and the algorithm of classification. In this paper, we revisited the topic of image representation. Classical descriptors such as Bag-of-Features are usually based on SIFT. We propose here an alternative based on bio-inspired features. This approach is inspired by a model of the retina which acts as an image filter to detect local contrasts. We show the promising results that we obtained in natural scenes classification with the proposed bio-inspired image representation.
Type de document :
Communication dans un congrès
KDIR - International Conference on Knowledge Discovery and Information Retrieval - 2011, 2011, Paris, France. pp.277-281, 2011
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https://hal.inria.fr/hal-00845745
Contributeur : Pierre Kornprobst <>
Soumis le : mercredi 17 juillet 2013 - 16:13:31
Dernière modification le : mercredi 14 décembre 2016 - 01:06:52

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Wafa Bel Haj Ali, Eric Debreuve, Pierre Kornprobst, Michel Barlaud. Bio-Inspired Bags-of-Features for Image Classification. KDIR - International Conference on Knowledge Discovery and Information Retrieval - 2011, 2011, Paris, France. pp.277-281, 2011. <hal-00845745>

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