van den Berg, R and Cornelissen, FW and Roerdink, JB (2009) A crowding model of visual clutter. J Vis, 9. 24.1-2411.Full text not available from this repository.
Visual information is difficult to search and interpret when the density of the displayed information is high or the layout is chaotic. Visual information that exhibits such properties is generally referred to as being "cluttered." Clutter should be avoided in information visualizations and interface design in general because it can severely degrade task performance. Although previous studies have identified computable correlates of clutter (such as local feature variance and edge density), understanding of why humans perceive some scenes as being more cluttered than others remains limited. Here, we explore an account of clutter that is inspired by findings from visual perception studies. Specifically, we test the hypothesis that the so-called "crowding" phenomenon is an important constituent of clutter. We constructed an algorithm to predict visual clutter in arbitrary images by estimating the perceptual impairment due to crowding. After verifying that this model can reproduce crowding data we tested whether it can also predict clutter. We found that its predictions correlate well with both subjective clutter assessments and search performance in cluttered scenes. These results suggest that crowding and clutter may indeed be closely related concepts and suggest avenues for further research.
|Uncontrolled Keywords:||Algorithms Contrast Sensitivity Humans Models, Neurological Orientation Pattern Recognition, Visual Photic Stimulation Visual Fields Visual Perception|
|Divisions:||Div F > Computational and Biological Learning|
|Depositing User:||Cron Job|
|Date Deposited:||15 Dec 2015 12:56|
|Last Modified:||30 Apr 2016 04:54|