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对合成噪声图像和艺术品的分形缩放特性的偏好。

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

作者信息

Viengkham Catherine, Spehar Branka

机构信息

Department of Psychology, University of New South Wales, Sydney, NSW, Australia.

出版信息

Front Psychol. 2018 Aug 29;9:1439. doi: 10.3389/fpsyg.2018.01439. eCollection 2018.

Abstract

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.

摘要

大量研究支持这样一种观点,即在一定的中间分形标度范围内的合成图像具有内在的美学价值。有趣的是,定义这个中间范围的分形标度特性也被发现是大量具象、抽象和图形艺术的特征。虽然有些人认为这些统计特性只是为了最大限度地提高艺术品空间结构的可见性,但另一些人则认为它们与艺术品的美学吸引力有着内在联系。在本研究中,我们将这两条研究线索结合起来,直接比较了合成图像和艺术品中不同分形标度特征的视觉偏好。在两项研究中,参与者对分形维数系统变化的合成噪声图像和艺术品集进行了排序和评分,评估其喜好程度、愉悦度、复杂度和有趣程度。我们分析了这两类图像之间的平均偏好模式和个体偏好模式。两类图像的平均偏好都在中间分形维数值时达到峰值,但也出现了对高分形维数和低分形维数的个体偏好模式。相关分析表明,这两类图像之间的个体偏好保持适度一致,并且当合成图像和艺术品之间的分形维数更紧密匹配时,偏好一致性会提高。总体而言,这些发现进一步支持了分形标度统计作为物体美学价值的关键决定因素以及美学偏好个体差异的重要预测指标的作用。

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