A Review of Automatic Lie Detection from Facial Features

IF 1.2 3区 心理学 Q4 PSYCHOLOGY, SOCIAL Journal of Nonverbal Behavior Pub Date : 2024-03-23 DOI:10.1007/s10919-024-00451-2
Hugues Delmas, Vincent Denault, Judee K. Burgoon, Norah E. Dunbar
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Abstract

The growth of machine learning and artificial intelligence has made it possible for automatic lie detection systems to emerge. These can be based on a variety of cues, such as facial features. However, there is a lack of knowledge about both the development and the accuracy of such systems. To address this lack, we conducted a review of studies that have investigated automatic lie detection systems by using facial features. Our analysis of twenty-eight eligible studies focused on four main categories: dataset features, facial features used, classifier features and publication features. Overall, the findings showed that automatic lie detection systems rely on diverse technologies, facial features, and measurements. They are mainly based on factual lies, regardless of the stakes involved. On average, these automatic systems were based on a dataset of 52 individuals and achieved an average accuracy ranging from 61.87% to 72.93% in distinguishing between truth-tellers and liars, depending on the types of classifiers used. However, although the leakage hypothesis was the most used explanatory framework, many studies did not provide sufficient theoretical justification for the choice of facial features and their measurements. Bridging the gap between psychology and the computational-engineering field should help to combine theoretical frameworks with technical advancements in this area.

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从面部特征自动检测谎言综述
随着机器学习和人工智能的发展,自动测谎系统应运而生。这些系统可以基于面部特征等各种线索。然而,人们对这类系统的开发和准确性都缺乏了解。为了解决这一问题,我们回顾了利用面部特征对自动测谎系统进行调查的研究。我们对 28 项符合条件的研究进行了分析,主要集中在四个方面:数据集特征、使用的面部特征、分类器特征和发布特征。总体而言,研究结果表明,自动测谎系统依赖于不同的技术、面部特征和测量方法。它们主要基于事实性谎言,而不考虑所涉及的利害关系。平均而言,这些自动系统以 52 个人的数据集为基础,在区分说真话者和说谎者方面达到了 61.87% 至 72.93% 的平均准确率,具体取决于所使用的分类器类型。然而,尽管泄漏假说是使用最多的解释框架,但许多研究并没有为面部特征的选择及其测量提供充分的理论依据。缩小心理学与计算工程领域之间的差距,有助于将理论框架与该领域的技术进步结合起来。
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
Journal of Nonverbal Behavior
Journal of Nonverbal Behavior PSYCHOLOGY, SOCIAL-
CiteScore
4.80
自引率
9.50%
发文量
27
期刊介绍: Journal of Nonverbal Behavior presents peer-reviewed original theoretical and empirical research on all major areas of nonverbal behavior. Specific topics include paralanguage, proxemics, facial expressions, eye contact, face-to-face interaction, and nonverbal emotional expression, as well as other subjects which contribute to the scientific understanding of nonverbal processes and behavior.
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