Generating customised experimental stimuli for visual search using Genetic Algorithms shows evidence for a continuum of search efficiency

被引：10

作者：

Verma, Milan ^{[1
]}

McOwan, Peter W. ^{[1
]}

机构：

[1] Queen Mary Univ London, Sch Elect Engn & Comp Sci, London, England

来源：

VISION RESEARCH | 2009年 / 49卷 / 03期

基金：

英国工程与自然科学研究理事会;

关键词：

Psychophysics; Pop-out; Saliency; Visual attention; Genetic Algorithms; SPATIAL-FREQUENCY; RECEPTIVE-FIELDS; MECHANISMS; ATTENTION; MODEL; DISCRIMINATION; SELECTIVITY; PERCEPTION; RESPONSES; SHIFTS;

D O I：

10.1016/j.visres.2008.11.006

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

Here we present a new empirically validated computational paradigm that generates on demand stimuli with user-defined levels of salience for use in visual search tasks. Combining a Genetic Algorithm with a biologically motivated model for image saliency we are able to breed a range of customised texture elements for use in psychophysical experiments. We review these psychophysical studies, showing for the first time that an explicit and predictable continuum of search efficiency exists in human visual search. (c) 2008 Elsevier Ltd. All rights reserved.

引用

页码：374 / 382

页数：9

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