Article

Artists portray human faces with the Fourier statistics of complex natural scenes

Institute of Anatomy I, School of Medicine, Friedrich Schiller University, Germany.
Network Computation in Neural Systems (Impact Factor: 0.87). 10/2007; 18(3):235-48. DOI: 10.1080/09548980701574496
Source: PubMed

ABSTRACT

When artists portray human faces, they generally endow their portraits with properties that render the faces esthetically more pleasing. To obtain insight into the changes introduced by artists, we compared Fourier power spectra in photographs of faces and in portraits by artists. Our analysis was restricted to a large set of monochrome or lightly colored portraits from various Western cultures and revealed a paradoxical result. Although face photographs are not scale-invariant, artists draw human faces with statistical properties that deviate from the face photographs and approximate the scale-invariant, fractal-like properties of complex natural scenes. This result cannot be explained by systematic differences in the complexity of patterns surrounding the faces or by reproduction artifacts. In particular, a moderate change in gamma gradation has little influence on the results. Moreover, the scale-invariant rendering of faces in artists' portraits was found to be independent of cultural variables, such as century of origin or artistic techniques. We suggest that artists have implicit knowledge of image statistics and prefer natural scene statistics (or some other rules associated with them) in their creations. Fractal-like statistics have been demonstrated previously in other forms of visual art and may be a general attribute of esthetic visual stimuli.

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Available from: Joachim Denzler, Mar 11, 2015
    • "In Study 2A, we investigated whether attractiveness and age perception is affected by superimposing specific statistical properties onto face images by overlaying them with random phase patterns. Based on the finding that visual artworks, including art portraits, and natural scenes share a Fourier slope of about -2[28,37,40], we expected that faces were perceived as more attractive and younger when overlaid with patterns with a slope of -2 or images with an overall shallower slope (overlaid with patterns with a slope of -1 or 0). Two groups of participants rated attractiveness and age, respectively, of faces in modified images in independent rating sessions. "
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    ABSTRACT: We investigated whether low-level processed image properties that are shared by natural scenes and artworks - but not veridical face photographs - affect the perception of facial attractiveness and age. Specifically, we considered the slope of the radially averaged Fourier power spectrum in a log-log plot. This slope is a measure of the distribution of special frequency power in an image. Images of natural scenes and artworks possess - compared to face images - a relatively shallow slope (i.e., increased high spatial frequency power). Since aesthetic perception might be based on the efficient processing of images with natural scene statistics, we assumed that the perception of facial attractiveness might also be affected by these properties. We calculated Fourier slope and other beauty-associated measurements in face images and correlated them with ratings of attractiveness and age of the depicted persons (Study 1). We found that Fourier slope - in contrast to the other tested image properties - did not predict attractiveness ratings when we controlled for age. In Study 2A, we overlaid face images with random-phase patterns with different statistics. Patterns with a slope similar to those in natural scenes and artworks resulted in lower attractiveness and higher age ratings. In Studies 2B and 2C, we directly manipulated the Fourier slope of face images and found that images with shallower slopes were rated as more attractive. Additionally, attractiveness of unaltered faces was affected by the Fourier slope of a random-phase background (Study 3). Faces in front of backgrounds with statistics similar to natural scenes and faces were rated as more attractive. We conclude that facial attractiveness ratings are affected by specific image properties. An explanation might be the efficient coding hypothesis.
    No preview · Article · Apr 2015 · PLoS ONE
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    • "For example, Redies et al. (2007b) and Schweinhart and Essock (in press) have shown that despite having broadly similar statistical regularities compared to natural scenes, portraits show differences in spatial frequency orientation compared to photographs of faces, and Hayn-Leichsenring et al. (2013) have shown that perceptual adaptation effects for faces and portraits do not transfer between domains. Redies et al. (2007b) argue that these kinds of discrepancies between faces and portraits can be explained in terms of the aesthetic appeal of natural scene-like statistical regularities. Thus, the second aim of the present study is to understand basic aesthetic properties of faces in portraiture. "
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    ABSTRACT: How do representations of the face in portraits relate to the natural face, and how does the aesthetics of portraits relate to the aesthetics of faces in photographs? Here we investigate these questions with regard to the frontal face. Frontal faces are of particular interest because they are by far the most commonly studied type of face image in psychology, yet frontal portraits have been little studied by psychologists. Using behavioral and statistical tests, we show that artistic representations of frontal female faces have representational properties that broadly match those of the natural face, but we also find properties unique to artworks. We report that, as with frontal faces, frontal portraits show norm-based coding properties with respect to preference: averaged portraits become more attractive in proportion to the number of portraits averaged together. However, averaged photographs of faces are preferred to averaged portraits, suggesting that faces in portraits and photographed faces show basic differences in aesthetics. Consistent with this notion, we found that average face width and height ratios in an extended sample of frontal female portraits were significantly different from those for photographed faces. This indicates that portraits on average are not faithful representations of the typical structure of the face. In a behavioral experiment where we manipulated the structural ratios in portraits, we found that the preferred width and height ratios were significantly different from those preferred in photographed faces, and that the preferred ratios for portraits were closer to the average ratios of the portrait sample. We evaluate a variety of possible causes of the observed differences. We conclude that despite the demonstrated differences between artistic representations and natural faces, fundamental properties of natural faces are preserved in artistic representations of the face.
    Full-text · Article · Jan 2014
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    • "The Fourier slope is not highly correlated with the self-similarity measure (Table 6). The Fourier slope of subsets of monochrome artworks and monochrome images of natural scenes share a slope value of around −2 (Graham and Field, 2007; Redies et al., 2007a,b; Alvarez-Ramirez et al., 2008), but the slope value of colored artworks converted to grayscale images is much lower (−2.8 in the "
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    ABSTRACT: Most visual advertisements are designed to attract attention, often by inducing a pleasant impression in human observers. Accordingly, results from brain imaging studies show that advertisements can activate the brain's reward circuitry, which is also involved in the perception of other visually pleasing images, such as artworks. At the image level, large subsets of artworks are characterized by specific statistical image properties, such as a high self-similarity and intermediate complexity. Moreover, some image properties are distributed uniformly across orientations in the artworks (low anisotropy). In the present study, we asked whether images of advertisements share these properties. To answer this question, subsets of different types of advertisements (single-product print advertisements, supermarket and department store leaflets, magazine covers and show windows) were analyzed using computer vision algorithms and compared to other types of images (photographs of simple objects, faces, large-vista natural scenes and branches). We show that, on average, images of advertisements and artworks share a similar degree of complexity (fractal dimension) and self-similarity, as well as similarities in the Fourier spectrum. However, images of advertisements are more anisotropic than artworks. Values for single-product advertisements resemble each other, independent of the type of product promoted (cars, cosmetics, fashion or other products). For comparison, we studied images of architecture as another type of visually pleasing stimuli and obtained comparable results. These findings support the general idea that, on average, man-made visually pleasing images are characterized by specific patterns of higher-order (global) image properties that distinguish them from other types of images. Whether these properties are necessary or sufficient to induce aesthetic perception and how they correlate with brain activation upon viewing advertisements remains to be investigated.
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