September 2018
Volume 18, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2018
A factor analytic approach reveals variability and consistency in perceived complexity ratings of landscape photographs
Author Affiliations
  • Alexander Bies
    Psychology, College of Behavioral and Health Sciences, Middle Tennessee State University
  • Whitney Tate
    Psychology, College of Behavioral and Health Sciences, Middle Tennessee State University
  • Richard Taylor
    Physics, College of Arts and Sciences, University of Oregon
  • Margaret Sereno
    Psychology, College of Arts and Sciences, University of Oregon
Journal of Vision September 2018, Vol.18, 386. doi:10.1167/18.10.386
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      Alexander Bies, Whitney Tate, Richard Taylor, Margaret Sereno; A factor analytic approach reveals variability and consistency in perceived complexity ratings of landscape photographs. Journal of Vision 2018;18(10):386. doi: 10.1167/18.10.386.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

We engage with novel scenes' complexity until we achieve recognition and comprehension, which is important for activities from object identification to aesthetic evaluation. The physical complexity of a scene can be described in a multitude of ways, but a lack of individual differences studies implies our field holds the assumption that complexity perception is a basic perceptual process, consistent across individuals. Here, we take an unconventional approach to factor analysis to answer the question of how universal or idiosyncratic individuals' perceptions of complexity really are. Twenty-five participants (16 females) rated 200 landscape photographs. Each participant rated all of the images on a particular quality that relates to complexity (e.g., intricacy or simplicity). Correlation matrix heatmaps revealed variability across individuals, with most individuals' ratings exhibiting correlations of moderate strength with respect to others' ratings. Confirmatory factor analyses revealed that, for most participants, sets of five individuals who rated a given quality (e.g., intricacy) showed fairly strong agreement with others who rated the same quality (as indicated by strong loadings and non-significant chi-square tests). With regard to the relationship between factors, some models were good fits and revealed strong relationships between latent constructs, while others did not. Similarly, poor fits were observed for confirmatory factor analyses that sampled from each rated quality group (i.e., one participant who rated intricacy, another who rated simplicity, etc.). Thus, perceived complexity appears to be a multifaceted construct that could support individual differences, depending upon the aspects of a scene to which an individual is attending. In addition to supporting the study of scene complexity, the factor analytic approach we took here can be applied broadly to other studies with large numbers of stimuli. Importantly, this allows for particular responses to be correlated, which provides insights into the cognitive processes involved in responding to the presented images.

Meeting abstract presented at VSS 2018

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