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Authors: Agni Delvinioti 1 ; Hervé Jégou 1 ; Laurent Amsaleg 2 and Michael Houle 3

Affiliations: 1 Inria, France ; 2 CNRS-IRISA, France ; 3 National Institute of Informatics, Japan

Keyword(s): Image Search, Reciprocal Nearest Neighbors, Shared Neighbors, Image Similarity.

Abstract: Content-based image retrieval systems typically rely on a similarity measure between image vector representations, such as in bag-of-words, to rank the database images in decreasing order of expected relevance to the query. However, the inherent asymmetry of k-nearest neighborhoods is not properly accounted for by traditional similarity measures, possibly leading to a loss of retrieval accuracy. This paper addresses this issue by proposing similarity measures that use neighborhood information to assess the relationship between images. First, we extend previous work on k-reciprocal nearest neighbors to produce new measures that improve over the original primary metric. Second, we propose measures defined on sets of shared nearest neighbors for reranking the shortlist. Both these methods are simple, yet they significantly improve the accuracy of image search engines on standard benchmark datasets.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Delvinioti, A.; Jégou, H.; Amsaleg, L. and Houle, M. (2014). Image Retrieval with Reciprocal and Shared Nearest Neighbors. In Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: VISAPP; ISBN 978-989-758-004-8; ISSN 2184-4321, SciTePress, pages 321-328. DOI: 10.5220/0004672303210328

@conference{visapp14,
author={Agni Delvinioti. and Hervé Jégou. and Laurent Amsaleg. and Michael Houle.},
title={Image Retrieval with Reciprocal and Shared Nearest Neighbors},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: VISAPP},
year={2014},
pages={321-328},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004672303210328},
isbn={978-989-758-004-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: VISAPP
TI - Image Retrieval with Reciprocal and Shared Nearest Neighbors
SN - 978-989-758-004-8
IS - 2184-4321
AU - Delvinioti, A.
AU - Jégou, H.
AU - Amsaleg, L.
AU - Houle, M.
PY - 2014
SP - 321
EP - 328
DO - 10.5220/0004672303210328
PB - SciTePress