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◆ PLoS Computational Biology2026-05-14· Window (computing)

Art’s hidden topology: A window into human perception

Emil Dmitruk, Beata Bajno, Lidia Kot, Joanna Dreszer, Bibianna Bałaj, Ewa Ratajczak, Marcin Hajnowski, Romuald A. Janik, Marek Kuś, Shabnam Kadir, Jacek Rogala

原始摘要(英文原文)· Original abstract
Generations of researchers have sought a link between features of an artistic image and the audience's experience. However, a direct link between the properties of an image and the responses evoked has still not been established. Given the importance of shape to human perception and artistic creation, it can be assumed that one of the most important aspects of an artistic image is the use of different visual structures. We show that a method from the field of computational topology, persistent homology, can be used to analyse properties of image structures and composition at multiple scales. In order to determine the reliability of this method as a tool for analysing visual artworks, we analysed two different sets of abstract paintings that revealed significant discrepancies in the eye tracking, electrical brain activity and the subjective experience of viewers. Our research showed that our newly developed method not only clearly distinguished between two sets of images but also allowed us to map topological features onto gaze fixation heat maps. Furthermore, the extent to which various artistic images violate a topological duality (Alexander duality) is significantly different from that of pseudo-art. It is intriguing that a diverse group of eminent abstract artists seem to favour a special rate of violation close to a specific value.
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