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Authors: Franco Alberto Cardillo ; Giuseppe Amato and Fabrizio Falchi

Affiliation: Consiglio Nazionale delle Ricerche, Italy

Keyword(s): Biologically-Inspired Vision, Visual Attention, Visual Saliency, Landmark Recognition, Object Recognition, Content-based Image Retrieval.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Early and Biologically-Inspired Vision ; Image and Video Analysis ; Visual Attention and Image Saliency

Abstract: Many novel applications in the field of object recognition and pose estimation have been built relying on local invariant features extracted from key points that rely on high-contrast regions of the images. The visual saliency of the those regions is not considered by state-of-the art detection algorithms that assume the user is interested in the whole image. In this paper we present the experimental results of the application of a biologically-inspired model of visual attention to the problem of local feature selection in landmark and object recognition tasks. The results show that the approach improves the accuracy of the classifier in the object recognition task and preserves a good accuracy in the landmark recognition task.

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Paper citation in several formats:
Cardillo, F.; Amato, G. and Falchi, F. (2013). Using Visual Attention in a CBIR System - Experimental Results on Landmark and Object Recognition Tasks. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2013) - Volume 1: VISAPP; ISBN 978-989-8565-47-1; ISSN 2184-4321, SciTePress, pages 468-471. DOI: 10.5220/0004299404680471

@conference{visapp13,
author={Franco Alberto Cardillo. and Giuseppe Amato. and Fabrizio Falchi.},
title={Using Visual Attention in a CBIR System - Experimental Results on Landmark and Object Recognition Tasks},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2013) - Volume 1: VISAPP},
year={2013},
pages={468-471},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004299404680471},
isbn={978-989-8565-47-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2013) - Volume 1: VISAPP
TI - Using Visual Attention in a CBIR System - Experimental Results on Landmark and Object Recognition Tasks
SN - 978-989-8565-47-1
IS - 2184-4321
AU - Cardillo, F.
AU - Amato, G.
AU - Falchi, F.
PY - 2013
SP - 468
EP - 471
DO - 10.5220/0004299404680471
PB - SciTePress

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