Nakauchi Shigeki, Tamura Hideki
Department of Computer Science and Engineering, Toyohashi University of Technology, 1-1 Hibarigaoka Tempaku, Toyohashi, Aichi, 441-8580, Japan.
Sci Rep. 2022 Aug 26;12(1):14585. doi: 10.1038/s41598-022-18847-9.
This study explores the role of colour statistics in painting preferences and tests the 'matching-to-nature' hypothesis which posits that the preference for the colour composition of paintings depends on the extent to which the paintings resemble the colour statistics of natural scenes. A preference judgement experiment was conducted with 31,353 participants using original and hue-rotated versions of 1,200 paintings. Multiple regression analyses were performed between the measured preferences and paintings' colour statistics to reveal which colour statistics explained the preference data and to what extent. The colour statistics of art paintings that explained the preference data were compared to the colour statistics of natural scenes. The results identified the colour statistics that significantly contributed to explaining painting preferences, and the distributions of the paintings' colour statistics systematically differed from those of natural scenes. These findings suggest that the human visual system encodes colour statistics to make aesthetic judgements based on the artistic merit of colour compositions, and not on their similarity to natural scenes.
本研究探讨了颜色统计在绘画偏好中的作用，并检验了“与自然匹配”假说，该假说认为对绘画颜色构成的偏好取决于绘画与自然场景颜色统计的相似程度。对31353名参与者进行了一项偏好判断实验，使用了1200幅绘画的原始版本和色调旋转版本。对测量出的偏好与绘画的颜色统计进行了多元回归分析，以揭示哪些颜色统计可以解释偏好数据以及解释程度如何。将解释偏好数据的艺术绘画的颜色统计与自然场景的颜色统计进行了比较。结果确定了对解释绘画偏好有显著贡献的颜色统计，并且绘画颜色统计的分布与自然场景的分布存在系统性差异。这些发现表明，人类视觉系统对颜色统计进行编码，以便基于颜色构成的艺术价值做出审美判断，而不是基于它们与自然场景的相似性。
