ArticleFrontiers in psychology2020
Global Image Properties Predict Ratings of Affective Pictures.
Article in Frontiers in psychology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Effect evaluation of integrating art education into medical aesthetics postgraduate training: a single-arm pre-post study.BMC medical education · 2026Article
- A toolbox for calculating quantitative image properties in aesthetics research.Behavior research methods · 2025Article
- The perceptual primacy of feeling: Affectless visual machines explain a majority of variance in human visually evoked affect.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Direct perception of affective valence from vision.Nature communications · 2024Article
- Emotional Overshadowing: Pleasant and Unpleasant Cues Overshadow Neutral Cues in Human Associative Learning.Affective science · 2024Article
- Validation of the open biological negative image set for a Portuguese population: Comparing Japanese and Portuguese samples and an exploration of low-order visual properties of the stimuli.Behavior research methods · 2024Article
- Self-Relevance Predicts the Aesthetic Appeal of Real and Synthetic Artworks Generated via Neural Style Transfer.Psychological science · 2023Article
- Chromatic and spatial image statistics predict infants' visual preferences and adults' aesthetic preferences for art.Journal of vision · 2023Article
- Statistical image properties and aesthetic judgments on abstract paintings by Robert Pepperell.Journal of vision · 2023Article
- Statistical image properties predict aesthetic ratings in abstract paintings created by neural style transfer.Frontiers in neuroscience · 2022Article
- Swipes and Saves: A Taxonomy of Factors Influencing Aesthetic Assessments and Perceived Beauty of Mobile Phone Photographs.Frontiers in psychology · 2022Review
- Contour features predict valence and threat judgements in scenes.Scientific reports · 2021Article
- Implicit Associations With Nature and Urban Environments: Effects of Lower-Level Processed Image Properties.Frontiers in psychology · 2021Article
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5 authors.
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Abstract
Affective pictures are widely used in studies of human emotions. The objects or scenes shown in affective pictures play a pivotal role in eliciting particular emotions. However, affective processing can also be mediated by low-level perceptual features, such as local brightness contrast, color or the spatial frequency profile. In the present study, we asked whether image properties that reflect global image structure and image composition affect the rating of affective pictures. We focused on 13 global image properties that were previously associated with the esthetic evaluation of visual stimuli, and determined their predictive power for the ratings of five affective picture datasets (IAPS, GAPED, NAPS, DIRTI, and OASIS). First, we used an SVM-RBF classifier to predict high and low ratings for valence and arousal, respectively, and achieved a classification accuracy of 58-76% in this binary decision task. Second, a multiple linear regression analysis revealed that the individual image properties account for between 6 and 20% of the variance in the subjective ratings for valence and arousal. The predictive power of the image properties varies for the different datasets and type of ratings. Ratings tend to share similar sets of predictors if they correlate positively with each other. In conclusion, we obtained evidence from non-linear and linear analyses that affective pictures evoke emotions not only by
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