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Authors: Björn Barz and Joachim Denzler

Affiliation: Friedrich Schiller University Jena, Germany

Keyword(s): Content-based Image Retrieval, Interactive Image Retrieval, Relevance Feedback.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Enterprise Information Systems ; Human and Computer Interaction ; Human-Computer Interaction

Abstract: Query images presented to content-based image retrieval systems often have various different interpretations, making it difficult to identify the search objective pursued by the user. We propose a technique for overcoming this ambiguity, while keeping the amount of required user interaction at a minimum. To achieve this, the neighborhood of the query image is divided into coherent clusters from which the user may choose the relevant ones. A novel feedback integration technique is then employed to re-rank the entire database with regard to both the user feedback and the original query. We evaluate our approach on the publicly available MIRFLICKR-25K dataset, where it leads to a relative improvement of average precision by 23% over the baseline retrieval, which does not distinguish between different image senses.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Barz, B. and Denzler, J. (2018). Automatic Query Image Disambiguation for Content-based Image Retrieval. In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 5: VISAPP; ISBN 978-989-758-290-5; ISSN 2184-4321, SciTePress, pages 249-256. DOI: 10.5220/0006593402490256

@conference{visapp18,
author={Björn Barz. and Joachim Denzler.},
title={Automatic Query Image Disambiguation for Content-based Image Retrieval},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 5: VISAPP},
year={2018},
pages={249-256},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006593402490256},
isbn={978-989-758-290-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 5: VISAPP
TI - Automatic Query Image Disambiguation for Content-based Image Retrieval
SN - 978-989-758-290-5
IS - 2184-4321
AU - Barz, B.
AU - Denzler, J.
PY - 2018
SP - 249
EP - 256
DO - 10.5220/0006593402490256
PB - SciTePress

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