Grebenkina Maria, Brachmann Anselm, Bertamini Marco, Kaduhm Ali, Redies Christoph
Experimental Aesthetics Group, Institute of Anatomy I, Jena University Hospital, School of Medicine, University of Jena, Jena, Germany.
Department of Psychological Sciences, University of Liverpool, Liverpool, United Kingdom.
Front Neurosci. 2018 Sep 28;12:678. doi: 10.3389/fnins.2018.00678. eCollection 2018.
We recently found that luminance edges are more evenly distributed across orientations in large subsets of traditional artworks, i.e., artworks are characterized by a relatively high entropy of edge orientations, when compared to several categories of other (non-art) images. In the present study, we asked whether edge-orientation entropy is associated with aesthetic preference in a wide variety of other man-made visual patterns and scenes. In the first (exploratory) part of the study, participants rated the aesthetic appeal of simple shapes, artificial ornamental patterns, facades of buildings, scenes of interior architecture, and music album covers. Results indicated that edge-orientation entropy predicts aesthetic ratings for these stimuli. However, the magnitude of the effect depended on the type of images analyzed, on the range of entropy values encountered, and on the type of aesthetic rating (, or ). For example, edge-orientation entropy predicted about half of the variance when participants rated facade photographs for and , but only for 3.5% of the variance for ratings of music album covers. We also asked whether edge-orientation entropy relates to the well-established human preference for curved over angular shapes. Our analysis revealed that edge-orientation entropy was as good or an even better predictor for the aesthetic ratings than curvilinearity. Moreover, entropy could substitute for , at least in part, to predict the aesthetic ratings. In the second (experimental) part of this study, we generated complex line stimuli that systematically varied in their edge-orientation entropy and curved/angular shape. Here, edge-orientation entropy was a more powerful predictor for ratings of and than curvilinearity, and as good a predictor for . Again, the two image properties shared a large portion of variance between them. In summary, our results indicate that edge-orientation entropy predicts aesthetic ratings in diverse man-made visual stimuli. Moreover, the preference for high edge-orientation entropy shares a large portion of predicted variance with the preference for curved over angular stimuli.
我们最近发现，与几类其他（非艺术）图像相比，在传统艺术作品的大子集中，亮度边缘在各个方向上分布得更为均匀，即艺术作品的特征是边缘方向具有相对较高的熵。在本研究中，我们探讨了边缘方向熵是否与各种其他人造视觉图案和场景中的审美偏好相关。在研究的第一部分（探索性部分），参与者对简单形状、人工装饰图案、建筑物外立面、室内建筑场景和音乐专辑封面的审美吸引力进行了评分。结果表明，边缘方向熵可预测这些刺激的审美评分。然而，这种效应的大小取决于所分析图像的类型、所遇到的熵值范围以及审美评分的类型（比如，或）。例如，当参与者对建筑物外立面照片进行和评分时，边缘方向熵预测了约一半的方差，但对于音乐专辑封面的评分，仅预测了3.5%的方差。我们还研究了边缘方向熵是否与人类对曲线形状优于角形形状的既定偏好有关。我们的分析表明，对于审美评分而言，边缘方向熵是与曲线度一样好甚至更好的预测指标。此外，熵至少在一定程度上可以替代曲线度来预测审美评分。在本研究的第二部分（实验部分），我们生成了边缘方向熵和曲线/角形形状系统变化的复杂线条刺激。在这里，对于和评分，边缘方向熵比曲线度是更有力的预测指标，对于评分两者效果相当。同样，这两种图像属性之间存在很大一部分方差共享。总之，我们的结果表明，边缘方向熵可预测各种人造视觉刺激中的审美评分。此外，对高边缘方向熵的偏好与对曲线形状优于角形刺激的偏好共享了很大一部分预测方差。
