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Authors: Foti Coleca 1 ; Sabrina Zîrnovean 2 ; Thomas Käster 3 ; Thomas Martinetz 1 and Erhardt Barth 1

Affiliations: 1 University of Lübeck, Germany ; 2 University of Lübeck and University "POLITEHNICA" of București, Germany ; 3 University of Lübeck and Pattern Recognition Company GmbH, Germany

Keyword(s): Object Recognition, Pet Recognition, Sparse Representations, End-stopped Operators, Higher-order Decorrelation, Deep Multi-layer Networks.

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: We present a biologically inspired algorithm for key-point detection based on multi-layer and nonlinear centersurround inhibition. A Bag-of-Visual-Words framework is used to evaluate the performance of the detector on the Oxford III-T Pet Dataset for pet recognition. The results demonstrate an increased performance of our algorithm compared to the SIFT key-point detector. We further improve the recognition rate by separately training codebooks for the ON- and OFF-type key points. The results show that our key-point detection algorithms outperform the SIFT detector by having a lower recognition-error rate over a whole range of different key-point densities. Randomly selected key-points are also outperformed.

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Paper citation in several formats:
Coleca, F.; Zîrnovean, S.; Käster, T.; Martinetz, T. and Barth, E. (2014). Key-point Detection with Multi-layer Center-surround Inhibition. In Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 2: VISAPP; ISBN 978-989-758-003-1; ISSN 2184-4321, SciTePress, pages 386-393. DOI: 10.5220/0004743103860393

@conference{visapp14,
author={Foti Coleca. and Sabrina Zîrnovean. and Thomas Käster. and Thomas Martinetz. and Erhardt Barth.},
title={Key-point Detection with Multi-layer Center-surround Inhibition},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 2: VISAPP},
year={2014},
pages={386-393},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004743103860393},
isbn={978-989-758-003-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 2: VISAPP
TI - Key-point Detection with Multi-layer Center-surround Inhibition
SN - 978-989-758-003-1
IS - 2184-4321
AU - Coleca, F.
AU - Zîrnovean, S.
AU - Käster, T.
AU - Martinetz, T.
AU - Barth, E.
PY - 2014
SP - 386
EP - 393
DO - 10.5220/0004743103860393
PB - SciTePress