Visual ambiguity plays a key role in the perceptual experience of art and has been much exploited by modernist and contemporary artists for aesthetic effects. But it remains unclear how aesthetic judgments are affected by visual ambiguity, and the subjective nature of aesthetic experience makes it difficult to measure. Wang et al. (2020) piloted a methodology in which a large collection of free-form textual descriptions of artworks were gathered from participants. The variability of these descriptions was then quantified computationally with Shannon entropy; ambiguous images tended to generate a greater number and wider diversity of descriptive terms. In the present study, we evaluated how well these measures can predict aesthetic preference for ambiguous images. We designed three crowdsourcing tasks in order to measure aesthetic preferences. The first was a simple rating task, and the other two required the participants to engage more actively with the images. We hypothesized that the number of associations evoked by ambiguous works of art, when computationally measured by entropy and description lengths, is a factor in judgments of their aesthetic value. Following this hypothesis, we made and tested a number of predictions. Our results provide broad support for the hypothesis, but with some interesting caveats and exceptions. We find that the form of the task significantly affects preference ratings and that participants’ responses can be clustered into two categories: those that prefer simple, recognizable imagery, and those that prefer more complex, ambiguous imagery. When taking this clustering into account, we find that our measures of entropy are correlated with aesthetic ratings. We conclude that these computational methods are useful for investigating the variable subjective responses to ambiguous artworks.

Preference for curvature has been demonstrated using many types of stimuli, but it remains an open question whether curvature plays a relevant role in responses to original artworks. To investigate this, a novel set of paintings was created, consisting of 3 variations—curved, sharp-angled, and mixed—of the same 16 indeterminate subjects. The present research aimed to differentiate between liking and wanting decisions. We assessed liking both online (study 1) and in the lab (study 2, task 2), using a continuous slider and a dichotomous forced choice, respectively. In both tasks, participants assigned higher ratings to the curved compared to the sharp-angled version of the paintings. Similarly, when participants were explicitly asked if they wanted to take the paintings home, they assigned higher wanting ratings to the curved version (study 2, task 3). However, when they were asked to act as a curator and select works they wanted for their gallery (study 2, task 4) and to make a physical effort to visually consume the painting (implicit wanting; study 2, task 1), no significant difference was found between the 3 sets of paintings. Finally, we found that explicit wanting decisions predicted liking for paintings, while implicit wanting and explicit liking predicted explicit wanting of the artworks in both the home and art contexts. This confirmed that it is possible to differentiate between liking and wanting responses to artistically relevant stimuli. We conclude that this theoretical distinction helps to explain previous conflicting results on the curvature effect, establishing a new line of research in the field of empirical aesthetics.

In the last two decades, contour shape has been widely studied as a factor in visual aesthetic preference. Many studies have shown that humans and other species usually prefer curved to sharp-angled contours. The reasons for this preference, although keenly debated, still remain unclear. Studies of preference for curvature have tended to rely on simple visual stimuli due to the need to control confounding variables, which has limited investigation of this effect in complex stimuli like artworks. Our objective in this study was to test whether the effect of preference for curvature can be extended to the art domain in an ecologically valid setting. We conducted two studies using original artworks exhibited in a museum context. Stimuli consisted of a series of 48 paintings divided into 16 sets with three versions in each set: one curved, one sharp-angled, and one mixed, while color, size and style were controlled for across each set. In both studies, we recorded participants’ preferred viewing distance and responses about liking and wanting the paintings. The results showed that participants looked at the curved paintings from a closer distance than the sharp-angled paintings, which we used as an implicit measure of approachability. Participants also liked and wanted the curved paintings significantly more than the sharp-angled paintings. We conclude that contour curvature is an important perceptual factor in people’s aesthetic judgements about artworks viewed in an ecologically valid setting.

Preference for curvature, the curvature effect, seems to transcend cultures, species and stimulus kinds. However, its nature and psychological mechanisms remain obscure because studies often overlook the complexity of contour characterisation and disregard personal and contextual factors. To investigate the curvature effect, we propose a continuous and multidimensional manipulation and contrasting experimental conditions examined at the group and individual levels that unveil a complex picture, not reducible to monotonous relationships: Perceptual and hedonic evaluations relied on multiple geometric features defining contour and shape. These features were specifically weighted to characterise each construct, depending on the individual and contingent on whether evaluating perceptually or hedonically. Crucially, the curvature effect was not robust to preference with respect to the median and continuous manipulations of contour for varying shapes. As curved contours are more easily perceived and processed than polygons, we hypothesised that perceived contour might explain liking for a figure beyond the effect of geometric features, finding that this association was subordinated to shape categorisations. Finally, domain-specific, personality and cognitive-preference traits moderated how people used each geometric feature in their perceptual and hedonic evaluations. We conclude that research on perception and appreciation of contour and shape should factor in their complexity and defining features. Additionally, embracing individual sensitivities opens potential avenues to advance the understanding of psychological phenomena. In summary, our approach unpacks a complex picture of contour preference that prompts critical reflections on past research and advice for future research, and it is applicable to other psychological constructs.

Despite its mathematical simplicity and ubiquity in imaging technology, there has long been doubt about the ability of linear perspective to best represent human visual space, especially at wide-angle fields of view under natural viewing conditions. We investigated whether changes to image geometry had an impact on participants’ performance, specifically in terms of non-metric distance estimates. Our multidisciplinary research team developed a new open-source image database to study distance perception in images by systematically manipulating target distance, field of view and image projection using non-linear natural projections. The database consists of 12 outdoor scenes of a virtual 3D urban environment in which a target ball is presented at increasing distance, visualised using both linear perspective and natural perspective images, rendered respectively with three different fields-of-view: 100, 120 and 140 degrees horizontally. In the first experiment (N=52) we tested the effects of linear vs. natural perspective on non-metric distance judgements. In the second experiment (N=195) we investigated the influence of contextual and previous familiarity with linear perspective, and individual differences in spatial skills on distance estimations. The results of both experiments showed that distance estimation accuracy improved in natural compared to linear perspective images, particularly at wide-angle fields-of-view. Moreover, undertaking a training session with only natural perspective images led to more accurate distance judgments overall. We argue that the efficacy of natural perspective may stem from its resemblance to the way objects appear under natural viewing conditions, and that this can provide insights into the phenomenological structure of visual space.