UNDERSTANDING FACE RECOGNITION

UNDERSTANDING FACE RECOGNITION
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DOI:
10.1111/j.2044-8295.1986.tb02199.x
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发表时间:
1986-08-01
影响因子:
4
通讯作者:
YOUNG, A
YOUNG, A
中科院分区:
心理学2区
文献类型:
--
作者:
BRUCE, V;YOUNG, A

文献摘要

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本文的目的是开发一个理论模型和一套术语来理解和讨论我们如何识别熟悉的人脸,以及识别与人脸处理的其他方面的关系。我们从看到的面孔中获得了七种不同类型的信息;这些信息被标记为图片、结构、视觉派生的语义、身份特定的语义、姓名、表情和面部语音编码。提出了一种功能模型,其中结构编码过程提供了适合于面部语音分析、表情分析和人脸识别单元的描述。熟悉面孔的识别涉及结构编码的产物与先前存储的描述熟悉面孔外观的结构代码之间的匹配,这些结构代码保存在面部识别单元中。然后从Person Identity节点访问特定于身份的语义码,并随后检索名称代码。也有人提出,认知系统在决定最初的匹配是否足够接近以表明真正的识别或仅仅是“相似之处”方面发挥了积极作用;有几个因素被认为影响了这种决定。这个功能模型用于收集来自不同来源的数据,包括实验室实验、对日常错误的研究,以及对不同类型脑损伤患者的研究。它还用于澄清负责对象、单词和人脸识别的过程之间的异同。
The aim of this paper is to develop a theoretical model and a set of terms for understanding and discussing how we recognize familiar faces, and the relationship between recognition and other aspects of face processing. It is suggested that there are seven distinct types of information that we derive from seen faces; these are labelled pictorial, structural, visually derived semantic, identity-specific semantic, name, expression and facial speech codes. A functional model is proposed in which structural encoding processes provide descriptions suitable for the analysis of facial speech, for analysis of expression and for face recognition units. Recognition of familiar faces involves a match between the products of structural encoding and previously stored structural codes describing the appearance of familiar faces, held in face recognition units. Identity-specific semantic codes are then accessed from person identity nodes, and subsequently name codes are retrieved. It is also proposed that the cognitive system plays an active role in deciding whether or not the initial match is sufficiently close to indicate true recognition or merely a ''resemblance''; several factors are seen as influencing such decisions. This functional model is used to draw together data from diverse sources including laboratory experiments, studies of everyday errors, and studies of patients with different types of cerebral injury. It is also used to clarify similarities and differences between processes responsible for object, word and face recognition.