# Analysis of the use of color and its emotional relationship in visual creations based on experiences during the context of the COVID-19 pandemic

arXiv: https://arxiv.org/abs/2203.13770 · HTML: https://mlsanity.com/paper/2203.13770/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 15 of its 127 references that are in the map.
- First posted on arXiv 25 Mar 2022.

## Builds on (most cited first, 15 of 15)

- [Deep Visual Domain Adaptation: A Survey](https://mlsanity.com/paper/1802.03601/) (2018)
- [CNN Features off-the-shelf: an Astounding Baseline for Recognition](https://mlsanity.com/paper/1403.6382/) (2014)
- [Large-scale Classification of Fine-Art Paintings: Learning The Right Metric on The Right Feature](https://mlsanity.com/paper/1505.00855/) (2015)
- [ArtEmis: Affective Language for Visual Art](https://mlsanity.com/paper/2101.07396/) (2021)
- [Affective Image Content Analysis: Two Decades Review and New Perspectives](https://mlsanity.com/paper/2106.16125/) (2021)
- [Learning Multi-level Deep Representations for Image Emotion Classification](https://mlsanity.com/paper/1611.07145/) (2016)
- [Instagram photos reveal predictive markers of depression](https://mlsanity.com/paper/1608.03282/) (2016)
- [Detecting People in Artwork with CNNs](https://mlsanity.com/paper/1610.08871/) (2016)
- [EmoNets: Multimodal deep learning approaches for emotion recognition in video](https://mlsanity.com/paper/1503.01800/) (2015)
- [Affective Computing for Large-Scale Heterogeneous Multimedia Data: A Survey](https://mlsanity.com/paper/1911.05609/) (2019)
- [Building Emotional Machines: Recognizing Image Emotions through Deep Neural Networks](https://mlsanity.com/paper/1705.07543/) (2017)
- [Image color transfer to evoke different emotions based on color combinations](https://mlsanity.com/paper/1307.3581/) (2013)
- [Colors -Messengers of Concepts: Visual Design Mining for Learning Color Semantics](https://mlsanity.com/paper/1505.06532/) (2015)
- [Extrapolating continuous color emotions through deep learning](https://mlsanity.com/paper/2009.04519/) (2020)
- [Quantitative analysis of visual representation of sign elements in COVID-19 context](https://mlsanity.com/paper/2112.08219/) (2021)

## Abstract (arXiv)

Color is a complex communicative element that helps us understand and evaluate our environment. At the level of artistic creation, this component influences both the formal aspects of the composition and the symbolic weight, directly affecting the construction and transmission of the message that you want to communicate, creating a specific emotional reaction. During the COVID-19 pandemic, people generated countless images transmitting this event's subjective experiences. Using the repository of images created in the Instagram account CAM (The COVID Art Museum), we propose a methodology to understand the use of color and its emotional relationship in this context. The process considers two stages in parallel that are then combined. First, emotions are extracted and classified from the CAM dataset images through a convolutional neural network. Second, we extract the colors and their harmonies through a clustering process. Once both processes are completed, we combine the results generating an expanded discussion on the usage of color, harmonies, and emotion. The results indicate that warm colors are prevalent in the sample, with a preference for analog compositions over complementary ones. The relationship between emotions and these compositions shows a trend in positive emotions, reinforced by the results of the algorithm a priori and the emotional relationship analysis of the attributes of color (hue, chroma, and lighting).