Predicting visual search performance by quantifying stimuli similarities

Predicting visual search performance by quantifying stimuli similarities

The effect of distractor homogeneity and target-distractor similarity on visual search was previously explored under two models designed for computer vision. We extend these models here to account for internal noise and to evaluate their ability to predict human performance. In four experiments, obs...

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Veröffentlicht in:Journal of vision (Charlottesville, Va.) Va.), 2008-04, Vol.8 (4), p.9.1-922
Hauptverfasser: Avraham, Tamar, Yeshurun, Yaffa, Lindenbaum, Michael
Format: Artikel
Sprache:eng
Schlagworte:
Attention - physiology
Humans
Models, Psychological
Orientation - physiology
Photic Stimulation
Psychophysics
Visual Perception - physiology
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container_title Journal of vision (Charlottesville, Va.)
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creator Avraham, Tamar
Yeshurun, Yaffa
Lindenbaum, Michael
description The effect of distractor homogeneity and target-distractor similarity on visual search was previously explored under two models designed for computer vision. We extend these models here to account for internal noise and to evaluate their ability to predict human performance. In four experiments, observers searched for a horizontal target among distractors of different orientation (orientation search; Experiments 1 and 2) or a gray target among distractors of different color (color search; Experiments 3 and 4). Distractor homogeneity and target-distractor similarity were systematically manipulated. We then tested our models' ability to predict the search performance of human observers. Our models' predictions were closer to human performance than those of other prominent quantitative models.
doi_str_mv 10.1167/8.4.9
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source MEDLINE; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals
subjects Attention - physiology
Humans
Models, Psychological
Orientation - physiology
Photic Stimulation
Psychophysics
Visual Perception - physiology
title Predicting visual search performance by quantifying stimuli similarities
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