Search

Set size and crowding affect search efficiency by limiting attention for recognition and attention against competition; however, these factors can be difficult to quantify in complex search tasks. The current experiments use a quantitative measure of the amount and variability of visual information (i.e., clutter) in highly complex stimuli (i.e., digital aeronautical charts) to examine limits of attention in visual search. Undergraduates at a large southern university searched for a target among 4, 8, or 16 distractors in charts with high, medium, or low global clutter. The target was in a high or low local-clutter region of the chart. In Experiment 1, reaction time increased as global clutter increased, particularly when the target was in a high local-clutter region. However, there was no effect of distractor set size, supporting the notion that global clutter is a better measure of attention against competition in complex visual search tasks. As a control, Experiment 2 demonstrated that increasing the number of distractors leads to a typical set size effect when there is no additional clutter (i.e., no chart). In Experiment 3, the effects of global and local clutter were minimized when the target was highly salient. When the target was nonsalient, more fixations were observed in high global clutter charts, indicating that the number of elements competing with the target for attention was also high. The results suggest design techniques that could improve pilots' search performance in aeronautical charts., (PsycINFO Database Record (c) 2010 APA, all rights reserved.)

Objective: A novel model of measuring clutter in complex geospatial displays was compared with human ratings of subjective clutter as a measure of convergence validity. The new model is called the color-clustering clutter (C3) model. Background: Clutter is a known problem in displays of complex data and has been shown to affect target search performance. Previous clutter models are discussed and compared with the C3 model. Method: Two experiments were performed. In Experiment 1, participants performed subjective clutter ratings on six classes of information visualizations. Empirical results were used to set two free parameters in the model. In Experiment 2, participants performed subjective clutter ratings on aeronautical charts. Both experiments compared and correlated empirical data to model predictions. Results: The first experiment resulted in a .76 correlation between ratings and C3. The second experiment resulted in a .86 correlation, significantly better than results from a model developed by Rosenholtz et al. Outliers to our correlation suggest further improvements to C3. Conclusions: We suggest that (a) the C3 model is a good predictor of subjective, impressions of clutter in geospatial displays, (b) geospatial clutter is a function of color density and saliency (primary C3 components), and (c) pattern analysis techniques could further improve C3. Application: The C3 model could be used to improve the design of electronic geospatial displays by suggesting when a display will be too cluttered for its intended audience. [ABSTRACT FROM AUTHOR]