Academic journal article Attention, Perception and Psychophysics

Automatic Guidance of Attention during Real-World Visual Search

Academic journal article Attention, Perception and Psychophysics

Automatic Guidance of Attention during Real-World Visual Search

Article excerpt

Published online: 22 April 2015

© The Psychonomic Society, Inc. 2015

Abstract Looking for objects in cluttered natural environments is a frequent task in everyday life. This process can be difficult, because the features, locations, and times of appearance of relevant objects often are not known in advance. Thus, a mechanism by which attention is automatically biased toward information that is potentially relevant may be helpful. We tested for such a mechanism across five experiments by engaging participants in real-world visual search and then assessing attentional capture for information that was related to the search set but was otherwise irrelevant. Isolated objects captured attention while preparing to search for objects from the same category embedded in a scene, as revealed by lower detection performance (Experiment 1A). This capture effect was driven by a central processing bottleneck rather than the withdrawal of spatial attention (Experiment 1B), occurred automatically even in a secondary task (Experiment 2A), and reflected enhancement of matching information rather than suppression of nonmatching information (Experiment 2B). Finally, attentional capture extended to objects that were semantically associated with the target category (Experiment 3). We conclude that attention is efficiently drawn towards a wide range of information that may be relevant for an upcoming real-world visual search. This mechanism may be adaptive, allowing us to find information useful for our behavioral goals in the face of uncertainty.

Keywords Attentional capture . Visual search . Scene perception

Introduction

Searching for things in our environment is a common task in everyday life. Searches can be directed toward different kinds of information, varying from individual objects (e.g., locating your shopping cart in a crowded grocery store) to entire object categories (e.g., finding fresh fruit in the produce section). The selection of relevant information in visual search is thought to be accomplished by matching incoming visual information to an internally generated attentional set (Bundesen, 1990; Duncan & Humphreys, 1989). Visual search appears to be most efficient when the exact appearance of a target is known in advance (Schmidt & Zelinsky, 2009;Wolfe,Horowitz, Kenner, Hyle, & Vasan, 2004), enabling observers to implement a detailed attentional set. In naturalistic settings, however, visual search is made difficult by a number of uncertainties that are inherent to our typical visual environment.

First, the appearance of any object in a scene is virtually unconstrained, because it depends on factors, such as the perspective from which it is viewed, its distance from the observer, and the degree to which it is occluded by other objects. Second, visual search performance suffers when targets share features with surrounding distracters (Duncan & Humphreys, 1989). This challenge is exacerbated in the real world, where the properties of both targets and nontargets are not always stable across time. For instance, which fruits and vegetables are available depends on the season. Third, the locations and points in time at which targets appear often are not known in advance.

The first two challenges suggest that searching for objects in the real world requires an abstract attentional set that is not bound to low-level features and can accommodate large variation in target and distracter appearance. The third challenge suggests that it would be adaptive to have mechanisms that automatically biasattentiontowardobjectsrelatedtothe search target so that they do not go unnoticed when they appear at unforeseen locations or times. The current research aimed to establish the existence of and investigate the properties of automatic capture by task-relevant information during real-world visual search that requires an abstract attentional set. For this purpose, we assessed the degree to which isolated and novel exemplars from an object category capture attention while participants prepare to detect the presence of objects rapidly from that category in subsequently presented natural scene photographs. …

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