Affiliation:
1. Johns Hopkins University, USA
Abstract
A plain, blank canvas does not look very beautiful; to make it aesthetically appealing requires adding structure and complexity. But how much structure is best? In other words, what is the relationship between beauty and complexity? It has long been hypothesized that complexity and beauty meet at a “sweet spot,” such that the most beautiful images are neither too simple nor too complex. Here, we take a novel experimental approach to this question, using an information-theoretic approach to object representation based on an internal “skeletal” structure. We algorithmically generated a library of two-dimensional polygons and manipulated their complexity by gradually smoothing out their features—essentially decreasing the amount of information in the objects. We then stylized these shapes as “paintings” by rendering them with artistic strokes, and “mounted” them on framed canvases hung in a virtual room. Participants were shown pairs of these mounted shapes (which possessed similar structures but varied in skeletal complexity) and chose which shape looked best by previewing each painting on the canvas. Experiment 1 revealed a “Goldilocks” effect: participants preferred paintings that were neither too simple nor too complex, such that moderately complex shapes were chosen as the most attractive paintings. Experiment 2 isolated the role of complexity per se: when the same shapes were scrambled (such that their structural complexity was undermined, while other visual features were preserved), the Goldilocks effect was dramatically diminished. These findings suggest a quadratic relationship between aesthetics and complexity in ways that go beyond previous measures of each and demonstrate the utility of information-theoretic approaches for exploring high-level aspects of visual experience.
Funder
National Science Foundation
Subject
Artificial Intelligence,Sensory Systems,Experimental and Cognitive Psychology,Ophthalmology
Cited by
5 articles.
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