Perceived beauty of random texture patterns: A preference for complexity

Friedenberg, Jay; Liby, Bruce W.

doi:10.1016/j.actpsy.2016.04.007

Cited by 39 publications

(42 citation statements)

References 13 publications

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“…dispersion) and this may explain the negative correlation with the British group. The preferences of British group appear to be consistent with a preference for intermediate density stimuli (Friedenberg & Liby, 2016), and the notion that people prefer patterns with high entropy and low algorithmic complexity (Gauvrit et al, 2017). We can only speculate given the lack of comparative data for our findings, but this notion may be reversed for the Egyptian group for certain patterns.…”

Section: Discussionsupporting

confidence: 70%

“…Observers showed a preference for polygons with greater complexity in contour length and in the number of concavities (Friedenberg & Bertamini, 2015); a correlation between GIF ratio and edge length suggesting a preference for intermediate density over the number of elements in binary chequerboard patterns (Friedenberg & Liby, 2016); and image compression of the contours in nonsense shapes correlated with subjective human judgments for the same shapes whilst avoiding familiarity biases (Forsythe, Mulhern, & Sawey, 2008). Gauvrit et al (2017) reanalysed the data from the study carried out by Friedenberg & Liby (2016) using entropy (in this context, entropy refers to the density of black and white cells in a pattern) and algorithmic complexity (GIF ratio and Block Decomposition Method) and Edge length (the complexity of the edge created by the cells, thus related to the 'crookedness' of the pattern) as additional measures of complexity. They found that people showed an overall preference for high entropy, and low algorithmic complexity, when controlling for entropy.…”

Section: Highlightsmentioning

confidence: 99%

“…As mentioned earlier, Birkhoff's polygons have been criticised because of possible associations with known objects and symbols. Abstract, non-figurative images are likely to contain fewer confounds than figurative images (Friedenberg & Liby, 2016;Forsythe et al, 2008).…”

Section: Highlightsmentioning

confidence: 99%

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A cross-cultural comparison for preference for symmetry: Comparing British and Egyptians non-experts

2017

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The aesthetic appeal of symmetry has been noted and discussed by artists, historians and scientists. To what extent this appeal is universal is a difficult question to answer. From a theoretical perspective, cross-cultural comparisons are important, because similarities would support the universality of the response to symmetry. Some pioneering work has focussed on comparisons between Britain and Egypt (Soueif & Eysenck, 1971, 1972), including both experts and naive subjects. These studies confirmed some degree of universal agreement in preferences for simple abstract symmetry. We revisited this comparison after almost half a century. We compared preferences of naïve students in Egypt (n = 200) and Britain (n= 200) for 6 different classes of symmetry in novel, abstract stimuli. We used three different measurements of complexity: Gif ratio, Edge length and the average cell size (average blob size, ABS). The results support Soueif & Eysenck's findings regarding preferences for reflectional and rotational symmetry, however they also throw new light on a greater preference for simplicity in Egyptian participants already noted by Soueif & Eysenck (1971).

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Section: Discussionsupporting

confidence: 70%

Section: Highlightsmentioning

confidence: 99%

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A cross-cultural comparison for preference for symmetry: Comparing British and Egyptians non-experts

2017

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“…For example, Güçlütürk et al (2016) generated geometric patterns using a computer algorithm that allowed them to precisely predefine the stimuli’s complexity as a function of decreasing shape size and rate at which the shapes filled a space. Such flexibility has allowed complexity to be variously defined across an equally vast array of visual objects, such as line drawings (Vitz, 1966), random polygons (Aitken, 1974; Martindale et al, 1990), grid textures (Ichikawa, 1985; Jacobsen, 2004; Friedenberg and Liby, 2016), abstract patterns (Gartus and Leder, 2017), and so forth. However, the lack of a consistent quantification has prevented researchers from reaching a definitive consensus regarding the place of complexity in esthetic appreciation (Nadal et al, 2010; Forsythe et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Preference for Fractal-Scaling Properties Across Synthetic Noise Images and Artworks

Viengkham

Špehar

2018

Front. Psychol.

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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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“…. Finally,Friedenberg and Liby (2016) selected twenty-five undergraduates (5 males and 20 female) from Manhattan College in New York to evaluate 10 images determined by the authors.…”

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confidence: 99%

Peer Review #3 of "Visual complexity modelling based on image features fusion of multiple kernels (v0.3)"

2019

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Humans' perception of visual complexity is often regarded as one of the key principles of aesthetic order, and is intimately related to the physiological, neurological and, possibly, psychological characteristics of the human mind. For these reasons, creating accurate computational models of visual complexity is a demanding task. Building upon on previous work in the field Forsythe et al. (2011); Machado et al. (2015) we explore the use of Machine Learning techniques to create computational models of visual complexity. For that purpose, we use a dataset composed of 800 visual stimuli divided into five categories, describing each stimulus by 329 features based on edge detection, compression error and Zipf's law. In an initial stage, a comparative analysis of representative state-of-the-art Machine Learning approaches is performed. Subsequently, we conduct an exhaustive outlier analysis. We analyze the impact of removing the extreme outliers, concluding that Feature Selection Multiple Kernel Learning obtains the best results, yielding an average correlation to humans' perception of complexity of 0.71 with only twenty-two features. These results outperform the current state-of-the-art, showing the potential of this technique for regression.

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Perceived beauty of random texture patterns: A preference for complexity

Cited by 39 publications

References 13 publications

A cross-cultural comparison for preference for symmetry: Comparing British and Egyptians non-experts

A cross-cultural comparison for preference for symmetry: Comparing British and Egyptians non-experts

Preference for Fractal-Scaling Properties Across Synthetic Noise Images and Artworks

Peer Review #3 of "Visual complexity modelling based on image features fusion of multiple kernels (v0.3)"

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