Visual search for complex objects: Set-size effects for faces, words and cars
- PMID: 31233767
- DOI: 10.1016/j.visres.2019.06.007
Visual search for complex objects: Set-size effects for faces, words and cars
Abstract
To compare visual processing for different object types, we developed visual search tests that generated accuracy and response time parameters, including an object set-size effect that indexes perceptual processing load. Our goal was to compare visual search for two expert object types, faces and visual words, as well as a less expert type, cars. We first asked if faces and words showed greater inversion effects in search. Second, we determined whether search with upright stimuli correlated with other perceptual indices. Last we assessed for correlations between tests within a single orientation, and between orientations for a single object type. Object set-size effects were smaller for faces and words than cars. All accuracy and temporal measures showed an inversion effect for faces and words, but not cars. Face-search accuracy measures correlated with accuracy on the Cambridge Face Memory Test and word-search temporal measures correlated with single-word reading times, but car search did not correlate with semantic car knowledge. There were cross-orientation correlations for all object types, as well as cross-object correlations in the inverted orientation, while in the upright orientation face search did not correlate with word or car search. We conclude that object search shows effects of expertise. Compared to cars, words and faces showed smaller object set-size effects, greater inversion effects, and their search results correlated with other indices of perceptual expertise. The correlation analyses provide preliminary evidence supporting contributions from common processes in the case of inverted stimuli, object-specific processes that operate in both orientations, and distinct processing for upright faces.
Keywords: Discrimination; Face recognition; Object recognition; Response time; Visual word recognition.
Copyright © 2019 Elsevier Ltd. All rights reserved.
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