A signal detection-based confidence-similarity model of face matching.

IF 5.1 1区 心理学 Q1 PSYCHOLOGY
Psychological review Pub Date : 2024-04-01 Epub Date: 2023-07-20 DOI:10.1037/rev0000435
Daniel Fitousi
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引用次数: 0

Abstract

Face matching consists of the ability to decide whether two face images (or more) belong to the same person or to different identities. Face matching is crucial for efficient face recognition and plays an important role in applied settings such as passport control and eyewitness memory. However, despite extensive research, the mechanisms that govern face-matching performance are still not well understood. Moreover, to date, many researchers hold on to the belief that match and mismatch conditions are governed by two separate systems, an assumption that likely thwarted the development of a unified model of face matching. The present study outlines a unified unequal variance confidence-similarity signal detection-based model of face-matching performance, one that facilitates the use of receiver operating characteristics (ROC) and confidence-accuracy plots to better understand the relations between match and mismatch conditions, and their relations to factors of confidence and similarity. A binomial feature-matching mechanism is developed to support this signal detection model. The model can account for the presence of both within-identities and between-identities sources of variation in face recognition and explains a myriad of face-matching phenomena, including the match-mismatch dissociation. The model is also capable of generating new predictions concerning the role of confidence and similarity and their intricate relations with accuracy. The new model was tested against six alternative competing models (some postulate discrete rather than continuous representations) in three experiments. Data analyses consisted of hierarchically nested model fitting, ROC curve analyses, and confidence-accuracy plots analyses. All of these provided substantial support in the signal detection-based confidence-similarity model. The model suggests that the accuracy of face-matching performance can be predicted by the degree of similarity/dissimilarity of the depicted faces and the level of confidence in the decision. Moreover, according to the model, confidence and similarity ratings are strongly correlated. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

基于信号检测的人脸匹配置信度-相似度模型
人脸匹配包括判断两张(或多张)人脸图像是属于同一个人还是属于不同身份的能力。人脸匹配对于高效的人脸识别至关重要,并在护照控制和目击者记忆等应用场合发挥着重要作用。然而,尽管进行了广泛的研究,人们对支配人脸匹配性能的机制仍不甚了解。此外,迄今为止,许多研究人员仍然认为匹配和不匹配条件是由两个不同的系统控制的,这一假设很可能阻碍了人脸匹配统一模型的发展。本研究概述了一个基于不等方差置信度-相似度信号检测的人脸匹配性能统一模型,该模型便于使用接收者操作特征图(ROC)和置信度-准确度图来更好地理解匹配和不匹配条件之间的关系,以及它们与置信度和相似度因素之间的关系。为支持这一信号检测模型,开发了一种二项式特征匹配机制。该模型可以解释人脸识别中存在的同一性内部和同一性之间的变化来源,并能解释大量的人脸匹配现象,包括匹配与不匹配的分离。该模型还能对置信度和相似度的作用及其与准确性的复杂关系做出新的预测。在三个实验中,新模型与六个可供选择的竞争模型(其中一些假设了离散而非连续的表征)进行了对比测试。数据分析包括分层嵌套模型拟合、ROC 曲线分析和置信度-准确度图分析。所有这些都为基于信号检测的置信度-相似度模型提供了大量支持。该模型表明,人脸匹配的准确性可以通过所描绘人脸的相似/不相似程度和决策的置信度来预测。此外,根据该模型,置信度和相似度评级密切相关。(PsycInfo Database Record (c) 2024 APA, 版权所有)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Psychological review
Psychological review 医学-心理学
CiteScore
9.70
自引率
5.60%
发文量
97
期刊介绍: Psychological Review publishes articles that make important theoretical contributions to any area of scientific psychology, including systematic evaluation of alternative theories.
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