Abstract
Aesthetics has been the subject of long-standing debates by philosophers and psychologists alike. In psychology, it is generally agreed that aesthetic experience results from an interaction between perception, cognition, and emotion. By experimental means, this triad has been studied in the field of experimental aesthetics, which aims to gain a better understanding of how aesthetic experience relates to fundamental principles of human visual perception and brain processes. Recently, researchers in computer vision have also gained interest in the topic, giving rise to the field of computational aesthetics. With computing hardware and methodology developing at a high pace, the modeling of perceptually relevant aspect of aesthetic stimuli has a huge potential. In this review, we present an overview of recent developments in computational aesthetics and how they relate to experimental studies. In the first part, we cover topics such as the prediction of ratings, style and artist identification as well as computational methods in art history, such as the detection of influences among artists or forgeries. We also describe currently used computational algorithms, such as classifiers and deep neural networks. In the second part, we summarize results from the field of experimental aesthetics and cover several isolated image properties that are believed to have a effect on the aesthetic appeal of visual stimuli. Their relation to each other and to findings from computational aesthetics are discussed. Moreover, we compare the strategies in the two fields of research and suggest that both fields would greatly profit from a joined research effort. We hope to encourage researchers from both disciplines to work more closely together in order to understand visual aesthetics from an integrated point of view.
Highlights
Dating back more than two thousand years ago, aesthetics has been the subject of debates by philosophers and other scholars alike
Besides the prediction of visual preference, there has been another trend in computational aesthetics, which tends to be more focused on artworks than on photography
We discussed recent progress in this field, which has become known as computational aesthetics
Summary
Dating back more than two thousand years ago, aesthetics has been the subject of debates by philosophers and other scholars alike. Fechner’s scientific (objective) view of aesthetics provided the basis for the newly emerging field of empirical aesthetics In this field, hypotheses regarding the perceived beauty of images, paintings or even every-day objects are proposed and tested experimentally for their validity. Another discipline of natural science that studies aesthetics is neuroaesthetics, a subfield of brain research In this field, modern imaging techniques, such as functional magnetic resonance imaging (fMRI), enable researcher to study the activation of brain regions when human observers view aesthetic stimuli (CelaConde et al, 2011; Chatterjee and Vartanian, 2014). Our review outlines a possible link between research on the objective (physical) properties of visual stimuli and experimental studies that take into account the subjective responses of humans to aesthetic stimuli, as originally proposed by Fechner. Topics include the prediction of ratings of photographs and paintings, the classification of images regarding their artist or style, computational methods for problems in art history, and, the investigation of statistical properties of aesthetically pleasing images and artworks
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