Department of Psychology, Aberystwyth University, Aberystwyth, UK.
Br J Psychol. 2011 Feb;102(1):49-70. doi: 10.1348/000712610X498958.
Visual complexity has been known to be a significant predictor of preference for artistic works for some time. The first study reported here examines the extent to which perceived visual complexity in art can be successfully predicted using automated measures of complexity. Contrary to previous findings the most successful predictor of visual complexity was Gif compression. The second study examined the extent to which fractal dimension could account for judgments of perceived beauty. The fractal dimension measure accounts for more of the variance in judgments of perceived beauty in visual art than measures of visual complexity alone, particularly for abstract and natural images. Results also suggest that when colour is removed from an artistic image observers are unable to make meaningful judgments as to its beauty.
视觉复杂性一直以来都是影响人们对艺术作品偏好的一个重要因素。本文首先探讨了使用视觉复杂性的自动测量方法来预测艺术作品的视觉复杂性的程度。与之前的研究结果相反,最成功的预测因素是 Gif 压缩。第二项研究则探讨了分形维数在多大程度上可以解释对视觉艺术的感知美的判断。分形维数比单纯的视觉复杂性测量更能解释对视觉艺术的感知美的判断的差异,尤其是对于抽象和自然图像。结果还表明,当从艺术图像中去除颜色时,观察者无法对其美做出有意义的判断。