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Article

The Analysis of Emotion Authenticity Based on Facial Micromovements

1
School of Design, Savannah College of Art and Design, Savannah, GA 31401, USA
2
Department of Human Centered Artificial Intelligence, Sangmyung University, Jongno-gu, Seoul 03016, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Mario Munoz-Organero
Sensors 2021, 21(13), 4616; https://doi.org/10.3390/s21134616
Received: 15 April 2021 / Revised: 11 June 2021 / Accepted: 2 July 2021 / Published: 5 July 2021
(This article belongs to the Special Issue Emotion Intelligence Based on Smart Sensing)
People tend to display fake expressions to conceal their true feelings. False expressions are observable by facial micromovements that occur for less than a second. Systems designed to recognize facial expressions (e.g., social robots, recognition systems for the blind, monitoring systems for drivers) may better understand the user’s intent by identifying the authenticity of the expression. The present study investigated the characteristics of real and fake facial expressions of representative emotions (happiness, contentment, anger, and sadness) in a two-dimensional emotion model. Participants viewed a series of visual stimuli designed to induce real or fake emotions and were signaled to produce a facial expression at a set time. From the participant’s expression data, feature variables (i.e., the degree and variance of movement, and vibration level) involving the facial micromovements at the onset of the expression were analyzed. The results indicated significant differences in the feature variables between the real and fake expression conditions. The differences varied according to facial regions as a function of emotions. This study provides appraisal criteria for identifying the authenticity of facial expressions that are applicable to future research and the design of emotion recognition systems. View Full-Text
Keywords: facial micromovement; emotion recognition; emotion authenticity facial micromovement; emotion recognition; emotion authenticity
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MDPI and ACS Style

Park, S.; Lee, S.W.; Whang, M. The Analysis of Emotion Authenticity Based on Facial Micromovements. Sensors 2021, 21, 4616. https://doi.org/10.3390/s21134616

AMA Style

Park S, Lee SW, Whang M. The Analysis of Emotion Authenticity Based on Facial Micromovements. Sensors. 2021; 21(13):4616. https://doi.org/10.3390/s21134616

Chicago/Turabian Style

Park, Sung, Seong W. Lee, and Mincheol Whang. 2021. "The Analysis of Emotion Authenticity Based on Facial Micromovements" Sensors 21, no. 13: 4616. https://doi.org/10.3390/s21134616

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