title: Revisiting Rossion and Pourtois with new ratings for automated complexity, familiarity, beauty, and encounter.
abstract: Differences between norm ratings collected when participants are asked to consider more than one picture characteristic are contrasted with the traditional methodological approaches of collecting ratings separately for image constructs. We present data that suggest that reporting normative data, based on methodological procedures that ask participants to consider multiple image constructs simultaneously, could potentially confounded norm data. We provide data for two new image constructs, beauty and the extent to which participants encountered the stimuli in their everyday lives. Analysis of this data suggests that familiarity and encounter are tapping different image constructs. The extent to which an observer encounters an object predicts human judgments of visual complexity. Encountering an image was also found to be an important predictor of beauty, but familiarity with that image was not. Taken together, these results suggest that continuing to collect complexity measures from human judgments is a pointless exercise. Automated measures are more reliable and valid measures, which are demonstrated here as predicting human preferences.
authors.affiliation: Department of Psychology, University of Liverpool, Liverpool, UK. a.forsythe@liv.ac.uk.
authors.forename: Alex
authors.initials: A
authors.lastname: Forsythe
authors.affiliation: Department of Psychology, Staffordshire University, Stoke-on-Trent, UK.
authors.forename: Nichola
authors.initials: N
authors.lastname: Street
authors.affiliation: Department of Psychology, Menoufia University, Al Minufya, Egypt.
authors.forename: Mai
authors.initials: M
authors.lastname: Helmy
mesh_terms: D001504:Beauty; D006801:Humans; D007600:Judgment; D010775:Photic Stimulation; D021641:Recognition, Psychology; D012016:Reference Values; D014796:Visual Perception
keywords: Complexity; Familiarity; Norms; Pictures