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Spontaneous Facial Expressions and Micro-expressions Coding: From Brain to Face

1. We derived the relationship between AU and emotion based on a data-driven analysis of 5,000 images from the RAF-AU database, along with the experience of professional coders. 2. We discussed the complex facial motor cortical network system that generates facial movement properties, detailing the...

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Autores principales: Dong, Zizhao, Wang, Gang, Lu, Shaoyuan, Li, Jingting, Yan, Wenjing, Wang, Su-Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8763852/
https://www.ncbi.nlm.nih.gov/pubmed/35058850
http://dx.doi.org/10.3389/fpsyg.2021.784834
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author Dong, Zizhao
Wang, Gang
Lu, Shaoyuan
Li, Jingting
Yan, Wenjing
Wang, Su-Jing
author_facet Dong, Zizhao
Wang, Gang
Lu, Shaoyuan
Li, Jingting
Yan, Wenjing
Wang, Su-Jing
author_sort Dong, Zizhao
collection PubMed
description 1. We derived the relationship between AU and emotion based on a data-driven analysis of 5,000 images from the RAF-AU database, along with the experience of professional coders. 2. We discussed the complex facial motor cortical network system that generates facial movement properties, detailing the facial nucleus and the motor system associated with facial expressions. 3. The supporting physiological theory for AU labeling of emotions is obtained by adding facial muscle movements patterns. 4. We present the detailed process of emotion labeling and the detection and recognition of AU. Based on the above research, the video's coding of spontaneous expressions and micro-expressions is concluded and prospected.
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spelling pubmed-87638522022-01-19 Spontaneous Facial Expressions and Micro-expressions Coding: From Brain to Face Dong, Zizhao Wang, Gang Lu, Shaoyuan Li, Jingting Yan, Wenjing Wang, Su-Jing Front Psychol Psychology 1. We derived the relationship between AU and emotion based on a data-driven analysis of 5,000 images from the RAF-AU database, along with the experience of professional coders. 2. We discussed the complex facial motor cortical network system that generates facial movement properties, detailing the facial nucleus and the motor system associated with facial expressions. 3. The supporting physiological theory for AU labeling of emotions is obtained by adding facial muscle movements patterns. 4. We present the detailed process of emotion labeling and the detection and recognition of AU. Based on the above research, the video's coding of spontaneous expressions and micro-expressions is concluded and prospected. Frontiers Media S.A. 2022-01-04 /pmc/articles/PMC8763852/ /pubmed/35058850 http://dx.doi.org/10.3389/fpsyg.2021.784834 Text en Copyright © 2022 Dong, Wang, Lu, Li, Yan and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Dong, Zizhao
Wang, Gang
Lu, Shaoyuan
Li, Jingting
Yan, Wenjing
Wang, Su-Jing
Spontaneous Facial Expressions and Micro-expressions Coding: From Brain to Face
title Spontaneous Facial Expressions and Micro-expressions Coding: From Brain to Face
title_full Spontaneous Facial Expressions and Micro-expressions Coding: From Brain to Face
title_fullStr Spontaneous Facial Expressions and Micro-expressions Coding: From Brain to Face
title_full_unstemmed Spontaneous Facial Expressions and Micro-expressions Coding: From Brain to Face
title_short Spontaneous Facial Expressions and Micro-expressions Coding: From Brain to Face
title_sort spontaneous facial expressions and micro-expressions coding: from brain to face
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8763852/
https://www.ncbi.nlm.nih.gov/pubmed/35058850
http://dx.doi.org/10.3389/fpsyg.2021.784834
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