title: Clutter perception is invariant to image size.
abstract: Two experiments evaluated the effect of retinal image size on the proto-object model of visual clutter perception. Experiment 1 had 20 participants order 90 small images of random-category real-world scenes from least to most cluttered. Aggregating these individual rankings into a single median clutter ranking and comparing it to a previously reported clutter ranking of larger versions of the identical scenes yielded a Spearman's ρ=.953 (p<.001), suggesting that relative clutter perception is largely invariant to image size. We then applied the proto-object model of clutter perception to these smaller images and obtained a clutter estimate for each. Correlating these estimates with the median behavioral ranking yielded a Spearman's ρ=.852 (p<.001), which we showed in a comparative analysis to be better than six other methods of estimating clutter. Experiment 2 intermixed large and small versions of the Experiment 1 scenes and had participants (n=18) again rank them for clutter. We found that median clutter rankings of these size-intermixed images were essentially the same as the small and large median rankings from Experiment 1, suggesting size invariance in absolute clutter perception. Moreover, the proto-object model again successfully captured this result. We conclude that both relative and absolute clutter perception is invariant to retinal image size. We further speculate that clutter perception is mediated by proto-objects-a preattentive level of visual representation between features and objects-and that using the proto-object model we may be able to glimpse into this pre-attentive world.
authors.affiliation: Department of Psychology, Stony Brook University, USA; Department of Computer Science, Stony Brook University, USA. Electronic address: Gregory.Zelinsky@stonybrook.edu.
authors.forename: Gregory J
authors.initials: GJ
authors.lastname: Zelinsky
authors.affiliation: Department of Computer Science, Stony Brook University, USA.
authors.forename: Chen-Ping
authors.initials: CP
authors.lastname: Yu
mesh_terms: D001288:Attention / Q000502:physiology*; D003441:Crowding; D005133:Eye Movements / Q000502:physiology*; D006801:Humans; D014796:Visual Perception / Q000502:physiology*
keywords: Color clustering; Image segmentation; Image size; Proto-objects; Superpixels; Visual clutter