Abstract
Models of aesthetic experience suggest cognitive processes including complexity perception are involved in forming aesthetic responses (essentially, the appreciation of beauty). Investigating the relationship between the constructs perceived complexity and aesthetic value allows us to better understand the relationship between cognitive processes that contribute to aesthetic responses and outcomes of that evaluative process. The present study aims to understand the relationship between perceived complexity and aesthetic responses. Twenty participants (13 female) were shown instructions indicating they would rate a series of images on a continuous scale from 0 (lowest) to 1 (highest) by clicking on a scale bar, and instructed to try to use the full range of the scale (not binary 0 or 1 responses) across trials. Each participant was then told the quality on which they should rate the images – a facet of complexity ("complexity" or "simplicity") or aesthetic value ("attractiveness" or "beauty"). Participants then rated each image sequentially, with image order randomized for each person. The images were a set of 200 black and white landscape photographs, taken with an AF-S DX NIKKOR 10-24mm lens set to 24mm affixed to a Nikon D7100 camera. Confirmatory factor analyses, in which each participant served as an "item" in a factor analysis where images were the "subjects," revealed that participants who rated the same property (e.g., simplicity) loaded on a single factor. We then analyzed the relationship between four pairs of complexity and aesthetic factors (e.g., "simplicity" and "attractiveness"), three of which provided a good fit with high factor loadings. The strong relationship between the latent constructs extracted from participants' responses indicates these are tightly coupled concepts. This suggests that for black and white photographs of landscapes, perceived complexity is largely sufficient to drive aesthetic responses, and that other theoretical paths are unnecessary.
Meeting abstract presented at VSS 2018