Sensitivity and validity of visual search models for multiple targets

Abstract

This study proposes two search models for multiple targets (random search and systematic search) in an unstructured search field, derived by generalizing search models for single target search. Whilst the probability of locating a single target in the random search model is typically exponentially distributed, the probability of locating multiple targets was found to be distributed hypo-exponentially. The systematic search model was extended from a piecewise-linear function for a single target to a piecewise-curve function for multiple targets. To test whether these search models could predict human search performance, first, visibility area in a fixation, a main component of search models, was investigated at various fixation durations. Sensitivity analysis of this data indicated that using short fixation duration and a small fixation overlap would produce better search performance. Next, the visibility area data was combined with the search models and compared to human performance on a free search field with three targets. The systematic and random models provided upper and lower boundaries of actual human search performance. Additionally, at the start of the search task for multiple targets, search performance was close to the systematic search model, while for late targets, performance approached the random search model. Observers may have changed their search strategy during this multiple-target visual search task.