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The Role of Low-Spatial Frequency Components in the Processing of Deceptive Faces: A Study Using Artificial Face Models

机译:低空间频率成分在欺骗性面孔处理中的作用:使用人工面孔模型的研究

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摘要

Interpreting another’s true emotion is important for social communication, even in the face of deceptive facial cues. Because spatial frequency components provide important clues for recognizing facial expressions, we investigated how we use spatial frequency information from deceptive faces to interpret true emotion. We conducted two different tasks: a face-generating experiment in which participants were asked to generate deceptive and genuine faces by tuning the intensity of happy and angry expressions (Experiment 1) and a face-classification task in which participants had to classify presented faces as either deceptive or genuine (Experiment 2). Low- and high-spatial frequency (LSF and HSF) components were varied independently. The results showed that deceptive happiness (i.e., anger is the hidden expression) involved different intensities for LSF and HSF. These results suggest that we can identify hidden anger by perceiving unbalanced intensities of emotional expression between LSF and HSF information contained in deceptive faces.
机译:诠释他人的真实情感对社交交流也很重要,即使面对欺骗性的面部表情也是如此。由于空间频率成分为识别面部表情提供了重要线索,因此我们研究了如何使用来自欺骗性面孔的空间频率信息来解释真实情感。我们执行了两个不同的任务:一个面部生成实验,其中要求参与者通过调整高兴和愤怒表情的强度来生成欺骗性的和真实的面孔(实验1);以及一个面部分类任务,其中参与者必须将呈现的面孔分类为具有欺骗性或真实性(实验2)。低空间频率和高空间频率(LSF和HSF)分量独立变化。结果表明,欺骗性幸福(即,愤怒是隐藏的表达)涉及LSF和HSF的不同强度。这些结果表明,我们可以通过感知欺骗性面孔中包含的LSF和HSF信息之间的情感表达强度不平衡来识别隐藏的愤怒。

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