A Multi-Criteria Approach for Gaze Analysis Similarity in Paintings

Tess Masclef, Mihaela Scuturici, Tetiana Yemelianenko, Serge Miguet

2025

Abstract

In the fields of art history and visual semiotics, analysing gazes in paintings is important to understand the artwork, and to find semantic relationships between several paintings. Thanks to digitization and museum initiatives, the volume of datasets on artworks continues to expand, enabling new avenues for exploration and research. Artificial neural networks, trained on large datasets are able to extract complex features, and visually compare artworks. This comparison could be done by focusing on the objects present in the paintings, and matching paintings with high object co-occurrence. Our research takes this further by studying the way objects are viewed by characters in the scene. This study proposes a new approach that combines methods for gaze-based and visual-based similarity, to encode and use gaze information for finding similar paintings, while maintaining a close visual aspect. Experimental results which integrate the opinions of domain experts, show that these methods complement each other. Quantitative and qualitative assessments confirm the results from the combination of gaze and visual analysis. Thus, this method improves existing visual similarity queries and opens up new possibilities to retrieve similar paintings according to user-specific criteria.

Paper Citation

in Harvard Style

Masclef T., Scuturici M., Yemelianenko T. and Miguet S. (2025). A Multi-Criteria Approach for Gaze Analysis Similarity in Paintings. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP; ISBN 978-989-758-728-3, SciTePress, pages 123-134. DOI: 10.5220/0013152800003912

in Bibtex Style

@conference{visapp25,
author={Tess Masclef and Mihaela Scuturici and Tetiana Yemelianenko and Serge Miguet},
title={A Multi-Criteria Approach for Gaze Analysis Similarity in Paintings},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2025},
pages={123-134},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013152800003912},
isbn={978-989-758-728-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP
TI - A Multi-Criteria Approach for Gaze Analysis Similarity in Paintings
SN - 978-989-758-728-3
AU - Masclef T.
AU - Scuturici M.
AU - Yemelianenko T.
AU - Miguet S.
PY - 2025
SP - 123
EP - 134
DO - 10.5220/0013152800003912
PB - SciTePress