Aesthetic Perception of Line Patterns: Effect of Edge-Orientation Entropy and Curvilinear Shape

Beauty and the sharp fangs of the beast: degree of angularity predicts perceived preference and threat

The evaluation of angular vs. curved forms has a long history in psychology but few of the many studies conducted have examined actual degree of angularity. In two experiments, we present observers with randomly positioned and randomly oriented texture displays of angles viewed within a circular frame. The angle conditions varied from 0° to 180° in 20° increments, covering the entire spectrum of possibilities including acute, obtuse, right, and straight line angles. In Experiment 1, 25 undergraduates rated the perceived beauty of these displays. In Experiment 2, the same stimulus set and procedure were used with 27 participants instead judging perceived threat. Based on the findings in the literature, we predicted that sharper angles would be judged less beautiful and more threatening. The results were mostly confirmed. Acute angles are preferred less but there are also distinct preferences for right angles and straight lines, perhaps due to their greater familiarity in constructed environments. There was a consistent and anticipated finding for threat in the second study: the sharper an angle, the greater its perceived threat. Fear of sharp objects as assessed in a personality questionnaire was found to positively correlate with threat judgements. Future work should look more closely at degree of angularity in embedded object contours and at individual response differences.

Statistical image properties predict aesthetic ratings in abstract paintings created by neural style transfer

Artificial intelligence has emerged as a powerful computational tool to create artworks. One application is Neural Style Transfer, which allows to transfer the style of one image, such as a painting, onto the content of another image, such as a photograph. In the present study, we ask how Neural Style Transfer affects objective image properties and how beholders perceive the novel (style-transferred) stimuli. In order to focus on the subjective perception of artistic style, we minimized the confounding effect of cognitive processing by eliminating all representational content from the input images. To this aim, we transferred the styles of 25 diverse abstract paintings onto 150 colored random-phase patterns with six different Fourier spectral slopes. This procedure resulted in 150 style-transferred stimuli. We then computed eight statistical image properties (complexity, self-similarity, edge-orientation entropy, variances of neural network features, and color statistics) for each image. In a rating study, we asked participants to evaluate the images along three aesthetic dimensions (Pleasing, Harmonious, and Interesting). Results demonstrate that not only objective image properties, but also subjective aesthetic preferences transferred from the original artworks onto the style-transferred images. The image properties of the style-transferred images explain 50 – 69% of the variance in the ratings. In the multidimensional space of statistical image properties, participants considered style-transferred images to be more Pleasing and Interesting if they were closer to a “sweet spot” where traditional Western paintings (JenAesthetics dataset) are represented. We conclude that NST is a useful tool to create novel artistic stimuli that preserve the image properties of the input style images. In the novel stimuli, we found a strong relationship between statistical image properties and subjective ratings, suggesting a prominent role of perceptual processing in the aesthetic evaluation of abstract images.

The Presence of a Visual Dividing Line Increases Consumer Memory Through Attention Grabbing

Marketers often use a visual line to divide the product information on an advertisement into left-right (or top-bottom) segments for aesthetic or categorization purposes. The present research examined the effect of the dividing line on the consumer memory. Across three studies (including an eye-tracking study and a field one), we showed that the presence of a dividing line enhances consumers’ memory about the products displayed on the left/top of an advertisement. This effect occurs because the dividing line orients participants’ first eye fixation to the left/top area of the advertisement, such that their visual attention is largely restricted to that area and they could better remember the contents displayed on that area. The theoretical contributions and implications for marketers and consumers are discussed.

Approximate Entropy in Canonical and Non-Canonical Fiction

Computational textual aesthetics aims at studying observable differences between aesthetic categories of text. We use Approximate Entropy to measure the (un)predictability in two aesthetic text categories, i.e., canonical fiction ('classics') and non-canonical fiction (with lower prestige). Approximate Entropy is determined for series derived from sentence-length values and the distribution of part-of-speech-tags in windows of texts. For comparison, we also include a sample of non-fictional texts. Moreover, we use Shannon Entropy to estimate degrees of (un)predictability due to frequency distributions in the entire text. Our results show that the Approximate Entropy values can better differentiate canonical from non-canonical texts compared with Shannon Entropy, which is not true for the classification of fictional vs. expository prose. Canonical and non-canonical texts thus differ in sequential structure, while inter-genre differences are a matter of the overall distribution of local frequencies. We conclude that canonical fictional texts exhibit a higher degree of (sequential) unpredictability compared with non-canonical texts, corresponding to the popular assumption that they are more 'demanding' and 'richer'. In using Approximate Entropy, we propose a new method for text classification in the context of computational textual aesthetics.

Shape familiarity modulates preference for curvature in drawings of common-use objects

Drawing is a way to represent common-use objects. The contour of an object is a salient feature that defines its identity. Preference for a contour (curved or angular) may depend on how familiar the resulting shape looks for that given object. In this research, we examined the influence of shape familiarity on preference for curved or sharp-angled drawings of common-use objects. We also examined the possibility that some individual differences modulated this preference. Preference for curvature was assessed with a liking rating task (Experiment 1) and with a two-alternative forced-choice task simulating approach/avoidance responses (Experiment 2). Shape familiarity was assessed with a familiarity selection task where participants selected the most familiar shape between the curved and the angular version for each object, or whether both shapes were equally familiar for the object. We found a consistent preference for curvature in both experiments. This preference increased when the objects with a curved shape were selected as the most familiar ones. We also found preference for curvature when participants selected the shape of objects as equally familiar. However, there was no preference for curvature or preference for angularity when participants selected the sharp-angled shapes as the most familiar ones. In Experiment 2, holistic and affective types of intuition predicted higher preference for curvature. Conversely, participants with higher scores in the unconventionality facet showed less preference for the curved drawings. We conclude that shape familiarity and individual characteristics modulate preference for curvature.