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Preference for Fractal-Scaling Properties Across Synthetic Noise Images and Artworks
Author(s) -
Catherine Viengkham,
Branka Špehar
Publication year - 2018
Publication title -
frontiers in psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.947
H-Index - 110
ISSN - 1664-1078
DOI - 10.3389/fpsyg.2018.01439
Subject(s) - fractal dimension , fractal , preference , fractal analysis , scaling , noise (video) , dimension (graph theory) , range (aeronautics) , statistic , psychology , artificial intelligence , computer science , mathematics , image (mathematics) , statistics , geometry , combinatorics , mathematical analysis , materials science , composite material
A large number of studies support the notion that synthetic images within a certain intermediate fractal-scaling range possess an intrinsic esthetic value. Interestingly, the fractal-scaling properties that define this intermediate range have also been found to characterize a vast collection of representational, abstract, and graphic art. While some have argued that these statistic properties only serve to maximize the visibility of the artworks’ spatial structure, others argue that they are intrinsically tied to the artworks’ esthetic appeal. In this study, we bring together these two threads of research and make a direct comparison between visual preference for varying fractal-scaling characteristics in both synthetic images and artworks. Across two studies, viewers ranked and rated sets of synthetic noise images and artworks that systematically varied in fractal dimension for liking, pleasantness, complexity, and interestingness. We analyzed both average and individual patterns of preference between the two image classes. Average preference peaked for intermediate fractal dimension values for both categories, but individual patterns of preferences for both high and low values also emerged. Correlational analyses indicated that individual preferences between the two image classes remained moderately consistent and were improved when the fractal dimensions between synthetic images and artworks were more closely matched. Overall, these findings further support the role of fractal-scaling statistics both as a key determinant of an object’s esthetic value and as a valuable predictor of individual differences in esthetic preference.

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