Natural forms, often characterized by irregularity and roughness, have a unique complexity that exhibit self-similarity across different spatial scales or levels of magnification. Our visual system is remarkably efficient in the processing of natural scenes and tuned to the multi-scale, fractal-like properties they possess. The fractal-like scaling characteristics are ubiquitous in many physical and biological domains, with recent research also highlighting their importance in aesthetic perception, particularly in the visual and, to some extent, auditory modalities. Given the multitude of fractal-like (...) scaling manifestations, we explore potential commonalities in the way they might affect aesthetic preference within and across different physical and sensory domains. We use a range of visual and tactile stimuli to explore the equivalence of fractal-scaling effects on aesthetic preferences within and across visual and tactile modalities. Our results suggest that, despite some superficial differences, the underlying dimensional structure mediating the preference across the two domains is remarkably similar. The qualitative nature of this dimensional structure as well as suggestions for future research are discussed. (shrink)

Some things look more complex than others. For example, a crenulate and richly organized leaf may seem more complex than a plain stone. What is the nature of this experience—and why do we have it in the first place? Here, we explore how object complexity serves as an efficiently extracted visual signal that the object merits further exploration. We algorithmically generated a library of geometric shapes and determined their complexity by computing the cumulative surprisal of their internal skeletons—essentially quantifying the (...) “amount of information” within each shape—and then used this approach to ask new questions about the perception of complexity. Experiments 1–3 asked what kind of mental process extracts visual complexity: a slow, deliberate, reflective process (as when we decide that an object is expensive or popular) or a fast, effortless, and automatic process (as when we see that an object is big or blue)? We placed simple and complex objects in visual search arrays and discovered that complex objects were easier to find among simple distractors than simple objects are among complex distractors—a classic search asymmetry indicating that complexity is prioritized in visual processing. Next, we explored the function of complexity: Why do we represent object complexity in the first place? Experiments 4–5 asked subjects to study serially presented objects in a self‐paced manner (for a later memory test); subjects dwelled longer on complex objects than simple objects—even when object shape was completely task‐irrelevant—suggesting a connection between visual complexity and exploratory engagement. Finally, Experiment 6 connected these implicit measures of complexity to explicit judgments. Collectively, these findings suggest that visual complexity is extracted efficiently and automatically, and even arouses a kind of “perceptual curiosity” about objects that encourages subsequent attentional engagement. (shrink)

Increasing psychophysical evidence suggests that specific image features - or statistics - can appear unpleasant or induce visual discomfort in humans. Such unpleasantness tends to be particularly profound if the image's amplitude spectrum deviates from the regular 1/f spatial-frequency falloff expected in natural scenes. Here, we show that profound unpleasant impressions also result if the orientation spectrum of the image becomes flatter. Using bandpass noise with variable orientation and spatial-frequency bandwidths, we found that unpleasantness ratings decreased with spatial- frequency bandwidth (...) but increased with orientation bandwidth. Similarly, a subsequent experiment revealed that sinusoidal modulations in the amplitude spectrum of 1/f noise along the spatial frequency increased unpleasantness, but modulations along the orientation decreased it. Given that natural scenes tend to have a linear slope along the spatial frequency but an uneven spectrum along the orientation dimension, our opposing results in the spatial-frequency and orientation domains commonly support the idea that images deviating from the spectral regularity of natural scenes can give rise to unpleasant impressions. (shrink)

Nature experiences usually lead to restorative effects, such as positive affective states and reduced stress. Even watching nature compared to urban images, which are known to differ in several image properties that are processed at early stages, can lead to such effects. One potential pathway explaining how the visual input alone evokes restoration is that image properties processed at early stages in the visual system evoke positive associations. To study these automatic bottom-up processes and the role of lower-level visual processing (...) involved in the restoring effects of nature, we conducted two studies. First, we analyzed nature and urban stimuli for a comprehensive set of image properties. Second, we investigated implicit associations in a dichotomous set of nature and urban images in three domains, namely, valence, mood, and stress restoration. To examine the role of lower-level processing in these associations, we also used stimuli that lacked the spatial information but retained certain image properties of the original photographs. While original nature images were associated with “good,” “positive mood,” and “restoration,” urban images were associated with “bad” and “stress.” The results also showed that image properties differ between our nature and urban images and that they contribute to the implicit associations with valence, although spatial information and therefore recognition of the environment remained necessary for positive associations. Moreover, lower-level processed image properties seem to play no or only minor roles for associations with mood and stress restoration. (shrink)

Digital images taken by mobile phones are the most frequent class of images created today. Due to their omnipresence and the many ways they are encountered, they require a specific focus in research. However, to date, there is no systematic compilation of the various factors that may determine our evaluations of such images, and thus no explanation of how users select and identify relatively “better” or “worse” photos. Here, we propose a theoretical taxonomy of factors influencing the aesthetic appeal of (...) mobile phone photographs. Beyond addressing relatively basic/universal image characteristics, perhaps more related to fast perceptual processing of an image, we also consider factors involved in the slower re-appraisal or deepened aesthetic appreciation of an image. We span this taxonomy across specific types of picture genres commonly taken—portraits of other people, selfies, scenes and food. We also discuss the variety of goals, uses, and contextual aspects of users of mobile phone photography. As a working hypothesis, we propose that two main decisions are often made with mobile phone photographs: Users assess images at a first glance—by swiping through a stack of images—focusing on visual aspects that might be decisive to classify them from “low quality” to “acceptable” to, in rare cases, “an exceptionally beautiful picture.” Users make more deliberate decisions regarding one’s “favorite” picture or the desire to preserve or share a picture with others, which are presumably tied to aspects such as content, framing, but also culture or personality, which have largely been overlooked in empirical research on perception of photographs. In sum, the present review provides an overview of current focal areas and gaps in research and offers a working foundation for upcoming research on the perception of mobile phone photographs as well as future developments in the fields of image recording and sharing technology. (shrink)

This article serves as a step-by-step guide of a new application of Q-methodology to investigate people’s preferences for multivariate stimuli. Q-methodology has been widely applied in fields such as sociology, education and political sciences but, despite its numerous advantages, it has not yet gained much attention from experimental psychologists. This may be due to the fact that psychologists examining preferences, often adopt stimuli resulting from a combination of characteristics from multiple variables, and in repeated measure designs. At present, Q methodology (...) has not been adapted to accommodate. We therefore developed a novel analysis procedure allowing Q-methodology to handle these conditions. We propose a protocol requiring five analyses of a decision process to estimate: the preference of stimuli, the dominance of variables, the individual differences, the interaction between individual differences and preference, and the interaction between individual differences and dominance. The guide comes with a script developed in R to run the five analyses; furthermore, we provide a case study with a detailed description of the procedure and corresponding results. This guide is particularly beneficial to conduct and analyze experiments in any research on people’s preferences, such as experimental aesthetics, prototype testing, visual perception, etc. (shrink)