Color-Emotion Associations in Art: Fuzzy Approach
Muragul Muratbekova, Pakizar Shamoi
TL;DR
This work tackles the problem of mapping colors in art to human emotions by introducing a fuzzy color palette framework. It builds 120 fuzzy colors across 10 emotions using the HSI color space and WikiArt annotations, then defuzzifies to a set of basic colors for emotion-based retrieval. The approach is validated via a 2AFC study (average hit rate ≈ 0.77) and quantified with a Jaccard similarity metric $J(E,I)=\frac{|E\cap I|}{|E\cup I|}$, demonstrating strong alignment with human perception. The results offer a scalable, interpretable method for emotion-aware art retrieval and have broader implications for marketing, design, and psychology.
Abstract
Art objects can evoke certain emotions. Color is a fundamental element of visual art and plays a significant role in how art is perceived. This paper introduces a novel approach to classifying emotions in art using Fuzzy Sets. We employ a fuzzy approach because it aligns well with human judgments' imprecise and subjective nature. Extensive fuzzy colors (n=120) and a broad emotional spectrum (n=10) allow for a more human-consistent and context-aware exploration of emotions inherent in paintings. First, we introduce the fuzzy color representation model. Then, at the fuzzification stage, we process the Wiki Art Dataset of paintings tagged with emotions, extracting fuzzy dominant colors linked to specific emotions. This results in fuzzy color distributions for ten emotions. Finally, we convert them back to a crisp domain, obtaining a knowledge base of color-emotion associations in primary colors. Our findings reveal strong associations between specific emotions and colors; for instance, gratitude strongly correlates with green, brown, and orange. Other noteworthy associations include brown and anger, orange with shame, yellow with happiness, and gray with fear. Using these associations and Jaccard similarity, we can find the emotions in the arbitrary untagged image. We conducted a 2AFC experiment involving human subjects to evaluate the proposed method. The average hit rate of 0.77 indicates a significant correlation between the method's predictions and human perception. The proposed method is simple to adapt to art painting retrieval systems. The study contributes to the theoretical understanding of color-emotion associations in art, offering valuable insights for various practical applications besides art, like marketing, design, and psychology.