Intrinsic position uncertainty impairs overt search performance

Abstract

Uncertainty regarding the position of the search target is a fundamental component of visual search. However, due to perceptual limitations of the human visual system, this uncertainty can arise from intrinsic, as well as extrinsic, sources. The current study sought to characterize the role of intrinsic position uncertainty (IPU) in overt visual search and to determine whether it significantly limits human search performance. After completing a preliminary detection experiment to characterize sensitivity as a function of visual field position, observers completed a search task that required localizing a Gabor target within a field of synthetic luminance noise. The search experiment included two clutter conditions designed to modulate the effect of IPU across search displays of varying set size. In the Cluttered condition, the display was tiled uniformly with feature clutter to maximize the effects of IPU. In the Uncluttered condition, the clutter at irrelevant locations was removed to attenuate the effects of IPU. Finally, we derived an IPU-constrained ideal searcher model, limited by the IPU measured in human observers. Ideal searchers were simulated based on the detection sensitivity and fixation sequences measured for individual human observers. The IPU-constrained ideal searcher predicted performance trends similar to those exhibited by the human observers. In the Uncluttered condition, performance decreased steeply as a function of increasing set size. However, in the Cluttered condition, the effect of IPU dominated and performance was approximately constant as a function of set size. Our findings suggest that IPU substantially limits overt search performance, especially in crowded displays.

Natural image clutter degrades overt search performance independently of set size

“…Regardless of whether it is extrinsic or intrinsic, position uncertainty impairs performance for detecting, discriminating, and localizing stimuli. This is indicated by decreases in detection and localization accuracy (Burgess & Ghandeharian, 1984;Eckstein, Thomas, effects of position uncertainty seem to persist in search tasks requiring eye movements (i.e., overt search tasks; Semizer & Michel, 2017).…”

“…However, its effect on performance can be observed by manipulating the visual environment. In a recent study, Semizer and Michel (2017) introduced an experimental technique that modulates the effects of intrinsic uncertainty independently of extrinsic uncertainty by manipulating the distribution of clutter in synthetic noise displays. Using this technique, the authors showed that intrinsic position uncertainty substantially limits overt search performance and that its effects are especially evident when the amount of extrinsic uncertainty is controlled.…”

“…Synthetic stimuli provide researchers with a great deal of flexibility and control, enabling them to manipulate individual stimulus features and to determine how these contribute to performance in a variety of tasks. In visual search, for example, measuring performance in synthetic search displays has allowed researchers to discover how observers use information about peripheral target visibility to select fixations (Geisler, Perry, & Najemnik, 2006;Najemnik & Geisler, 2005;Najemnik & Geisler, 2008;Michel & Geisler, 2009;Verghese, 2012;Zhang & Eckstein, 2010), how intrinsic position uncertainty and clutter in the periphery degrade performance (Michel & Geisler, 2011;Rosenholtz, Huang, Raj, Balas, & Ilie, 2012;Semizer & Michel, 2017), how the template for known search targets is structured (Eckstein, Beutter, Pham, Shimozaki, & Stone, 2007), and how observers integrate information about the target across fixations (Caspi, Beutter, & Eckstein, 2004;Kleene & Michel, 2018), all while controlling extraneous properties of the search display (e.g., spectral spatial frequency statistics, environmental contingencies, target location probabilities, etc.) in ways that would be difficult or impossible with natural scenes.…”

“…This increase in set size augments the position uncertainty because of extrinsic sources. At the same time, because of intrinsic sources of position uncertainty, the ability to exclude irrelevant signals in the periphery decreases in highly cluttered scenes (Michel & Geisler, 2011;Semizer & Michel, 2017). These two concurrent effects of clutter make it challenging to separate the contributions of extrinsic versus intrinsic uncertainty on performance in highly cluttered images.…”

“…The goal of the current study was to separate out the contributions of intrinsic versus extrinsic sources of position uncertainty and to characterize them in a naturalistic search task that requires searching natural images for categorical targets. We approached this goal by controlling and manipulating set size independently of clutter, as in Semizer and Michel (2017). Instead of imposing synthetic clutter, we used an existing clutter measure (Bravo & Farid, 2008), chosen for its efficiency and its demonstrated correlation with search performance, to quantify the existing clutter in a set of natural images.…”