Gestalts Relate Aesthetic Preferences to Perceptual Analysis

ERC (European Research Council)HORIZON-ERCID: 101053925
EC Contribution
€24,977
Consortium Size
1 orgs
Start Year
2022
Summary

"De gustibus et coloribus non disputandum est."" With this slogan philosophers and lay people alike have dismissed all attempts to understand taste, color perception, or aesthetic preferences. Sense of beauty may just be too individual and too complex to qualify as target of scientific inquiry. Yet, since Fechner (1876), empirical aesthetics has studied the factors determining people’s aesthetic responses to art works and objects, scenes or events encountered in everyday life. Most accounts focus either on high-level concepts such as style, meaning and personal associations, or on low-level statistical properties. While the latter are supposed to be universal and biologically determined, the former are subject to cultural influences, art expertise and individual experiences. Progress in this tradition has reached its limits, which this project overcomes by investigating how Gestalts Relate Aesthetic Preferences to Perceptual Analysis (GRAPPA). Its pioneering working hypothesis is that the way perceivers organize their sensory inputs into meaningful entities (Gestalts) provides the missing link between the two traditional sets of explanations. This hypothesis is fleshed out and tested in a coherent research program linking aesthetic preferences for images of paintings and everyday photographs to general principles of perceptual organization as well as to specific aesthetic concepts like composition, balance and visual rightness. New data from online studies with large samples of images and participants will be analyzed with state-of-the-art computational methods (machine learning) to reveal the critical mid-level factors. This will yield a model to predict aesthetic preference, which will be tested in well-controlled psychophysical and behavioral experiments (e.g., eye-movement recording) and validated also in ecologically richer settings (e.g., in galleries and art museums) and in unconventional cross-over collaborations with contemporary artists.""

Consortium (1)

Project Results (8)

Source: CORDIS, the EU research results database.

Publications (6)
A toolbox for calculating quantitative image properties in aesthetics research
Behavior Research Methods· 2025DOI
Christoph Redies, Ralf Bartho, Lisa Koßmann, Branka Spehar, Ronald Hübner, Johan Wagemans, Gregor U. Hayn-Leichsenring
BackFlip: The Impact of Local and Global Data Augmentations on Artistic Image Aesthetic Assessment
Lecture Notes in Computer Science, Computer Vision – ECCV 2024 Workshops· 2025DOI
Ombretta Strafforello, Gonzalo Muradas Odriozola, Fatemeh Behrad, Li-Wei Chen, Anne-Sofie Maerten, Derya Soydaner, Johan Wagemans
Investigating the Gestalt Principle of Closure in Deep Convolutional Neural Networks
ESANN 2024 proceedings· 2024DOI
Zhang, Yuyan; Soydaner, Derya; Behrad, Fatemeh; Koßmann, Lisa; Wagemans, Johan
Multi-Task Convolutional Neural Network for Image Aesthetic Assessment
IEEE Access· 2024DOI
Derya Soydaner; Johan Wagemans
Unveiling the factors of aesthetic preferences with explainable AI
British Journal of Psychology· 2024DOI
Derya Soydaner; Johan Wagemans
Beautification of images by generative adversarial networks
Journal of Vision· 2023DOI
Amar Music; Anne-Sofie Maerten; Johan Wagemans
Deliverables (1)
Data Management Plan
Other Results (1)
Periodic Reporting for period 1 - GRAPPA (Gestalts Relate Aesthetic Preferences to Perceptual Analysis)