Suppr超能文献

构建一个跨种族面部身份三联测试。

Constructing a cross-race face identity triad test.

作者信息

Jeckeln Géraldine, O'Toole Alice J

机构信息

School of Behavioral and Brain Sciences, The University of Texas at Dallas, GR41, 800 W. Campbell Road, Richardson, TX, 75080, USA.

出版信息

Behav Res Methods. 2025 Sep 5;57(10):278. doi: 10.3758/s13428-025-02809-w.

Abstract

Despite the challenges associated with cross-race face identification, there are no publicly available tests of people's ability to identify own- versus other-race faces. We introduce the Cross-Race Face Identity Triad (CR-FIT) test, designed to be challenging for individuals of varying abilities. A key methodological advantage of the CR-FIT test over other face identity matching tests is that it eliminates response bias in face-identity matching through the use of face-image triads. A triad of face images includes two images of the same person and one image of a different person; participants must select the image of the "different" person. A second advantage of the CR-FIT test is that it ensures comparable difficulty for face stimuli from two races (African American, AA, Caucasian, CA) by leveraging machine and human pre-screening of items. This prescreening assures that performance differences reflect own- versus other-race identity matching ability, rather than differences in stimulus set difficulty. Triads were pre-screened to be challenging based on the performance of a publicly available face-identification algorithm. Items were further screened for comparability of difficulty using the performance of AA and CA observers. The test yields a classic "other-race effect"- observers identify own-race faces more accurately than other-race faces, with no effect of item race. Performance for untrained participants exceeded chance, but was far below ceiling, making the test suitable for a wide range of face identity matching abilities. The CR-FIT test is publicly available in an open science platform for research purposes.

摘要

尽管跨种族面部识别存在诸多挑战,但目前尚无公开可用的测试来检验人们识别自己种族与其他种族面孔的能力。我们推出了跨种族面部身份三联体(CR-FIT)测试,该测试旨在对不同能力的个体构成挑战。与其他面部身份匹配测试相比,CR-FIT测试的一个关键方法优势在于,它通过使用面部图像三联体消除了面部身份匹配中的反应偏差。一组面部图像三联体包括同一个人的两张图像和另一个人的一张图像;参与者必须选择“不同”人的图像。CR-FIT测试的第二个优势是,通过利用机器和人工对项目的预筛选,它确保了来自两个种族(非裔美国人,AA;白种人,CA)的面部刺激具有可比的难度。这种预筛选确保了表现差异反映的是自己种族与其他种族身份匹配能力,而非刺激集难度的差异。根据一种公开可用的面部识别算法的表现,对面部图像三联体进行预筛选,使其具有挑战性。利用非裔美国人和白种人观察者的表现,进一步筛选项目以确保难度的可比性。该测试产生了经典的“其他种族效应”——观察者识别自己种族面孔比识别其他种族面孔更准确,且不受项目种族的影响。未经训练的参与者的表现超过了随机水平,但远未达到上限,这使得该测试适用于广泛的面部身份匹配能力。CR-FIT测试在一个开放科学平台上公开提供,供研究使用。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验