Recognizing famous people
Recognizing famous people
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DOI：
10.3758/app.72.6.1444
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发表时间：
2010-08-01
影响因子：
1.7
通讯作者：
Fiset, Daniel
中科院分区：
文献类型：
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作者：
Butler, Sean;Blais, Caroline;Fiset, Daniel
在日常生活中，人脸识别需要观察者从记忆中的数百个甚至数千个代表中选择一个。这种选择的广度几乎不可能在实验室中使用新学习的面孔复制，特别是在泡沫实验的背景下（Gosselin & Schyns，2001）。在这项研究中，我们通过使用210张名人的面孔来研究观察者在面孔命名任务中的表现，从而消除了这种担忧。在每一次试验中，我们都展示了一张随机抽样的泡泡脸。我们对样本的位置和准确性进行了最小二乘多元线性回归，以确定在这项任务中有效使用的面部特征。正确的面部识别主要依赖于眼睛区域的空间频带范围从4.37到70周每面（cpf）和嘴和鼻子的空间频带范围从8.75到17.5 cpf。与其他研究的比较（Caldara等人，2005年的年度报告; Schyns，Bonnar，& Gosselin，2002），其中Bubbles与一组10个新学习的面孔一起使用，显示尽管眼睛区域在整个研究中是有用的，但当使用很少的新学习的面孔时，嘴部区域和更高的空间频率变得重要。
In daily life, face identification requires that the observer select a single representation from hundreds if not thousands in memory. This breadth of choice is nearly impossible to replicate in the laboratory using newly learned faces, especially in the context of a Bubbles experiment (Gosselin & Schyns, 2001). In this study, we obviated this concern by studying the performance of observers in a face-naming task using 210 faces of celebrities. On each trial, we presented a face randomly sampled with Bubbles. We performed least-square multiple linear regressions on the location of the samples and on accuracy to pinpoint the facial features that were used effectively in this task. Correct face identification relied primarily on the eye areas in spatial frequency bands ranging from 4.37 to 70 cycles per face (cpf) and on the mouth and the nose in a spatial frequency band ranging from 8.75 to 17.5 cpf. A comparison with other studies (Caldara et al., 2005; Schyns, Bonnar, & Gosselin, 2002) in which Bubbles was used with a set of 10 newly learned faces revealed that although the eye areas were useful across studies, the mouth area and higher spatial frequencies gained in importance when few newly learned faces were used.