research-article

Who's Afraid of Itten: Using the Art Theory of Color Combination to Analyze Emotions in Abstract Paintings

Authors:

Andreza Sartori,

Dubravko Culibrk,

Nicu SebeAuthors Info & Claims

MM '15: Proceedings of the 23rd ACM international conference on Multimedia

Pages 311 - 320

https://doi.org/10.1145/2733373.2806250

Published: 13 October 2015 Publication History

Abstract

Color plays an essential role in everyday life and is one of the most important visual cues in human perception. In abstract art, color is one of the essential means to convey the artist's intention and to affect the viewer emotionally. However, colors are rarely experienced in isolation, rather, they are usually presented together with other colors. In fact, the expressive properties of two-color combinations have been extensively studied by artists. It is intriguing to try to understand how color combinations in abstract paintings might affect the viewer emotionally, and to investigate if a computer algorithm can learn this mechanism.

In this work, we propose a novel computational approach able to analyze the color combinations in abstract paintings and use this information to infer whether a painting will evoke positive or negative emotions in an observer. We exploit art theory concepts to design our features and the learning algorithm. To make use of the color-group information, we propose inferring the emotions elicited by paintings based on the sparse group lasso approach. Our results show that a relative improvement of between 6% and 8% can be achieved in this way. Finally, as an application, we employ our method to generate Mondrian-like paintings and do a prospective user study to evaluate the ability of our method as an automatic tool for generating abstract paintings able to elicit positive and negative emotional responses in people.

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Cited By

Carrasco MGonzález-Martín CNavajas-Torrente SDastres R(2024)Level of Agreement between Emotions Generated by Artificial Intelligence and Human Evaluation: A Methodological ProposalElectronics10.3390/electronics1320401413:20(4014)Online publication date: 12-Oct-2024
https://doi.org/10.3390/electronics13204014
Xi DHu XYang LYang NLiu YJiang H(2023)Research on map emotional semantics using deep learning approachCartography and Geographic Information Science10.1080/15230406.2023.217208150:5(465-480)Online publication date: 21-Feb-2023
https://doi.org/10.1080/15230406.2023.2172081
Wang XYang JHu MRen F(2023)EERCA-ViT: Enhanced Effective Region and Context-Aware Vision Transformers for image sentiment analysisJournal of Visual Communication and Image Representation10.1016/j.jvcir.2023.10396897(103968)Online publication date: Dec-2023
https://doi.org/10.1016/j.jvcir.2023.103968
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Who's Afraid of Itten: Using the Art Theory of Color Combination to Analyze Emotions in Abstract Paintings

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Published In

cover image ACM Conferences

MM '15: Proceedings of the 23rd ACM international conference on Multimedia

October 2015

1402 pages

ISBN:9781450334594

DOI:10.1145/2733373

General Chairs:
Xiaofang Zhou
The University of Queensland, Australia
,
Alan F. Smeaton
Dublin City University, Ireland
,
Qi Tian
The University of Texas at San Antonio, USA
,
Program Chairs:
Dick C.A. Bulterman
FXPAL, USA
,
Heng Tao Shen
The University of Queensland, Australia
,
Ketan Mayer-Patel
The University of North Carolina, USA
,
Shuicheng Yan
National University of Singapore, Singapore

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 October 2015

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MM '15: ACM Multimedia Conference

October 26 - 30, 2015

Brisbane, Australia

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MM '15 Paper Acceptance Rate 56 of 252 submissions, 22%;

Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

Carrasco MGonzález-Martín CNavajas-Torrente SDastres R(2024)Level of Agreement between Emotions Generated by Artificial Intelligence and Human Evaluation: A Methodological ProposalElectronics10.3390/electronics1320401413:20(4014)Online publication date: 12-Oct-2024
https://doi.org/10.3390/electronics13204014
Xi DHu XYang LYang NLiu YJiang H(2023)Research on map emotional semantics using deep learning approachCartography and Geographic Information Science10.1080/15230406.2023.217208150:5(465-480)Online publication date: 21-Feb-2023
https://doi.org/10.1080/15230406.2023.2172081
Wang XYang JHu MRen F(2023)EERCA-ViT: Enhanced Effective Region and Context-Aware Vision Transformers for image sentiment analysisJournal of Visual Communication and Image Representation10.1016/j.jvcir.2023.10396897(103968)Online publication date: Dec-2023
https://doi.org/10.1016/j.jvcir.2023.103968
Li YFan ZZhu YYan CZhang K(2023)Comparing color usage in abstract, oil, and Chinese ink paintingsJournal of Visualization10.1007/s12650-023-00929-z26:6(1389-1404)Online publication date: 22-Jun-2023
https://doi.org/10.1007/s12650-023-00929-z
da Fonseca CSá ARibeiro Gagliardi Tdos Santos Alves MAyala Valencia G(2023)Understanding the packaging colour on consumer perception of plant‐based hamburgers: A preliminary studyPackaging Technology and Science10.1002/pts.272536:6(495-503)Online publication date: 17-Mar-2023
https://doi.org/10.1002/pts.2725
Fan ZZhu YYan CLi YZhang K(2022)A Comparative Study of Color Between Abstract Paintings, Oil Paintings and Chinese Ink PaintingsProceedings of the 15th International Symposium on Visual Information Communication and Interaction10.1145/3554944.3554951(1-8)Online publication date: 16-Aug-2022
https://dl.acm.org/doi/10.1145/3554944.3554951
Xu LWang ZWu BLui S(2022)MDAN: Multi-level Dependent Attention Network for Visual Emotion Analysis2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52688.2022.00926(9469-9478)Online publication date: Jun-2022
https://doi.org/10.1109/CVPR52688.2022.00926
Usha Kingsly Devi KGomathi V(2022)Deep Convolutional Neural Networks with Transfer Learning for Visual Sentiment AnalysisNeural Processing Letters10.1007/s11063-022-11082-355:4(5087-5120)Online publication date: 18-Nov-2022
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Yang HFan YLv GLiu SGuo Z(2022)Exploiting emotional concepts for image emotion recognitionThe Visual Computer10.1007/s00371-022-02472-839:5(2177-2190)Online publication date: 24-Apr-2022
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Sant'Anna Ados Santos Alves MMoraes Monteiro CRibeiro Gagliardi TAyala Valencia G(2022)The influence of packaging colour on consumer expectations of coffee using free word associationPackaging Technology and Science10.1002/pts.2675Online publication date: 17-Jun-2022
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