Robust Social Categorization Emerges From Learning the Identities of Very Few Faces
Robust Social Categorization Emerges From Learning the Identities of Very Few Faces
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DOI：
10.1037/rev0000048
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发表时间：
2017-03-01
影响因子：
5.4
通讯作者：
Burton, A. Mike
中科院分区：
文献类型：
--
作者：
Kramer, Robin S. S.;Young, Andrew W.;Burton, A. Mike
观众从面孔中识别性别和种族的准确率很高，尽管目前还不清楚这是如何实现的。熟悉面孔的识别在非常大的观看条件范围内也是高度准确的，尽管问题很困难。在这里，我们表明，性别和种族的计算可以偶然出现从一个系统设计来计算身份。我们强调与少数人多次相遇的作用，我们认为这是人脸学习的基础。我们使用几个人的高度可变的日常“环境”图像来训练线性判别分析（LDA）模型。由此产生的模型具有类似人类的特性，包括一种将以前看不见的熟悉（训练）人的环境图像融合在一起的能力，这种能力在未知（未训练）人的面孔上会崩溃。由身份训练的LDA创建的第一个维度按性别对熟悉和不熟悉的面孔进行分类，第二个维度按种族对面孔进行分类-即使这些类别都没有在学习中明确编码。通过改变的数量和类型的面孔身份上的进一步一系列的LDA模型进行了训练，我们表明，这种附带学习的性别和种族反映了这些社会类别和面孔的身份之间的协变，和一个非常小的身份需要学习之前，这种附带的尺寸出现。学习识别熟悉面孔的任务足以创建某些突出的社会类别。
Viewers are highly accurate at recognizing sex and race from faces-though it remains unclear how this is achieved. Recognition of familiar faces is also highly accurate across a very large range of viewing conditions, despite the difficulty of the problem. Here we show that computation of sex and race can emerge incidentally from a system designed to compute identity. We emphasize the role of multiple encounters with a small number of people, which we take to underlie human face learning. We use highly variable everyday 'ambient' images of a few people to train a Linear Discriminant Analysis (LDA) model on identity. The resulting model has human-like properties, including a facility to cohere previously unseen ambient images of familiar (trained) people-an ability which breaks down for the faces of unknown (untrained) people. The first dimension created by the identity-trained LDA classifies both familiar and unfamiliar faces by sex, and the second dimension classifies faces by race-even though neither of these categories was explicitly coded at learning. By varying the numbers and types of face identities on which a further series of LDA models were trained, we show that this incidental learning of sex and race reflects covariation between these social categories and face identity, and that a remarkably small number of identities need be learnt before such incidental dimensions emerge. The task of learning to recognize familiar faces is sufficient to create certain salient social categories.