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格子图案的视觉搜索不对称性。

A visual search asymmetry for plaids.

作者信息

Solomon Joshua A, Morgan Michael J, Chubb Charles F

机构信息

School of Health & Medical Sciences, City St George's, University of London, UK.

University of California, Irvine, California, United States.

出版信息

Perception. 2025 Aug;54(8):637-643. doi: 10.1177/03010066251340285. Epub 2025 May 30.

DOI:10.1177/03010066251340285
PMID:40448322
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12238659/
Abstract

Search asymmetry has been called a "litmus test" for basic visual features. The letter Q is thought to contain a basic feature because () it can be found quickly, no matter how many O's it is hiding amongst and () it is much harder to find an O amongst Q's. We tested the possibility that a basic visual feature is created when two perpendicular Gabor patterns are superimposed to form a "plaid." We found relatively large effects of set size on reaction time whenever participants tried to find a Gabor hiding among plaids. Set-size effects were smaller when participants tried to find a 2- or 4-cycle-per-degree plaid that was hiding among its component Gabors. The implication is that these plaids contain a basic visual feature, which is not present in its component Gabors. This feature may be an intrinsic two-dimensionality that is extracted from the visual intensity map. Mixed-frequency plaids did not pop out from their component Gabors. This last result suggests that the visual system separates intrinsically two-dimensional image regions (e.g., corners and junctions) from intrinsically one-dimensional image regions (e.g., straight edges) after the scene is segregated into parallel spatial frequency channels.

摘要

搜索不对称性被称为基本视觉特征的“石蕊试纸测试”。字母Q被认为包含一种基本特征,因为(1)无论它藏在多少个字母O中间,都能很快被找到;(2)而要在字母Q中间找到一个字母O则要难得多。我们测试了一种可能性,即当两个垂直的伽柏图案叠加形成一个“格子图案”时,会产生一种基本视觉特征。我们发现,每当参与者试图在格子图案中找到一个隐藏的伽柏图案时,刺激集大小对反应时间有相对较大的影响。当参与者试图在其组成伽柏图案中找到一个每度2或4个周期的格子图案时,刺激集大小的影响较小。这意味着这些格子图案包含一种基本视觉特征,而这种特征在其组成伽柏图案中并不存在。这种特征可能是从视觉强度图中提取的一种内在二维性。混合频率的格子图案不会从其组成伽柏图案中突显出来。最后这个结果表明,在场景被分离为平行的空间频率通道后,视觉系统会将内在二维图像区域(如角和交叉点)与内在一维图像区域(如直线边缘)区分开来。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd2/12238659/6a99b268776e/10.1177_03010066251340285-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd2/12238659/a6bcf893f27a/10.1177_03010066251340285-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd2/12238659/cd0bed6dddbe/10.1177_03010066251340285-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd2/12238659/a2eb94cc61e9/10.1177_03010066251340285-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd2/12238659/6a99b268776e/10.1177_03010066251340285-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd2/12238659/a6bcf893f27a/10.1177_03010066251340285-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd2/12238659/cd0bed6dddbe/10.1177_03010066251340285-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd2/12238659/a2eb94cc61e9/10.1177_03010066251340285-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd2/12238659/6a99b268776e/10.1177_03010066251340285-fig4.jpg

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