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Authors: Adam Vandor 1 ; Marie Van Vollenhoven 2 ; Gerhard Weiss 1 and Gerasimos Spanakis 1

Affiliations: 1 Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, The Netherlands ; 2 Infinity Games, Maastricht, The Netherlands

Keyword(s): Artistic Compositions, Feature Extraction, Machine Learning.

Abstract: Harmony in visual compositions is a concept that cannot be defined or easily expressed mathematically, even by humans. The goal of the research described in this paper was to find a numerical representation of artistic compositions with different levels of harmony. We ask humans to rate a collection of grayscale images based on the harmony they convey. To represent the images, a set of special features were designed and extracted. By doing so, it became possible to assign objective measures to subjectively judged compositions. Given the ratings and the extracted features, we utilized machine learning algorithms to evaluate the efficiency of such representations in a harmony classification problem. The best performing model (SVM) achieved 80% accuracy in distinguishing between harmonic and disharmonic images, which reinforces the assumption that concept of harmony can be expressed in a mathematical way that can be assessed by humans.

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Paper citation in several formats:
Vandor, A.; Van Vollenhoven, M.; Weiss, G. and Spanakis, G. (2021). Can We Detect Harmony in Artistic Compositions? A Machine Learning Approach. In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-484-8; ISSN 2184-433X, SciTePress, pages 187-195. DOI: 10.5220/0010244901870195

@conference{icaart21,
author={Adam Vandor. and Marie {Van Vollenhoven}. and Gerhard Weiss. and Gerasimos Spanakis.},
title={Can We Detect Harmony in Artistic Compositions? A Machine Learning Approach},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2021},
pages={187-195},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010244901870195},
isbn={978-989-758-484-8},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - Can We Detect Harmony in Artistic Compositions? A Machine Learning Approach
SN - 978-989-758-484-8
IS - 2184-433X
AU - Vandor, A.
AU - Van Vollenhoven, M.
AU - Weiss, G.
AU - Spanakis, G.
PY - 2021
SP - 187
EP - 195
DO - 10.5220/0010244901870195
PB - SciTePress

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