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Kinematic dataset of actors expressing emotions
Human body movements can convey a variety of emotions and even create advantages in some special life situations. However, how emotion is encoded in body movements has remained unclear. One reason is that there is a lack of public human body kinematic dataset regarding the expressing of various emot...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7478954/ https://www.ncbi.nlm.nih.gov/pubmed/32901035 http://dx.doi.org/10.1038/s41597-020-00635-7 |
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author | Zhang, Mingming Yu, Lu Zhang, Keye Du, Bixuan Zhan, Bin Chen, Shaohua Jiang, Xiuhao Guo, Shuai Zhao, Jiafeng Wang, Yang Wang, Bin Liu, Shenglan Luo, Wenbo |
author_facet | Zhang, Mingming Yu, Lu Zhang, Keye Du, Bixuan Zhan, Bin Chen, Shaohua Jiang, Xiuhao Guo, Shuai Zhao, Jiafeng Wang, Yang Wang, Bin Liu, Shenglan Luo, Wenbo |
author_sort | Zhang, Mingming |
collection | PubMed |
description | Human body movements can convey a variety of emotions and even create advantages in some special life situations. However, how emotion is encoded in body movements has remained unclear. One reason is that there is a lack of public human body kinematic dataset regarding the expressing of various emotions. Therefore, we aimed to produce a comprehensive dataset to assist in recognizing cues from all parts of the body that indicate six basic emotions (happiness, sadness, anger, fear, disgust, surprise) and neutral expression. The present dataset was created using a portable wireless motion capture system. Twenty-two semi-professional actors (half male) completed performances according to the standardized guidance and preferred daily events. A total of 1402 recordings at 125 Hz were collected, consisting of the position and rotation data of 72 anatomical nodes. To our knowledge, this is now the largest emotional kinematic dataset of the human body. We hope this dataset will contribute to multiple fields of research and practice, including social neuroscience, psychiatry, computer vision, and biometric and information forensics. |
format | Online Article Text |
id | pubmed-7478954 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-74789542020-09-21 Kinematic dataset of actors expressing emotions Zhang, Mingming Yu, Lu Zhang, Keye Du, Bixuan Zhan, Bin Chen, Shaohua Jiang, Xiuhao Guo, Shuai Zhao, Jiafeng Wang, Yang Wang, Bin Liu, Shenglan Luo, Wenbo Sci Data Data Descriptor Human body movements can convey a variety of emotions and even create advantages in some special life situations. However, how emotion is encoded in body movements has remained unclear. One reason is that there is a lack of public human body kinematic dataset regarding the expressing of various emotions. Therefore, we aimed to produce a comprehensive dataset to assist in recognizing cues from all parts of the body that indicate six basic emotions (happiness, sadness, anger, fear, disgust, surprise) and neutral expression. The present dataset was created using a portable wireless motion capture system. Twenty-two semi-professional actors (half male) completed performances according to the standardized guidance and preferred daily events. A total of 1402 recordings at 125 Hz were collected, consisting of the position and rotation data of 72 anatomical nodes. To our knowledge, this is now the largest emotional kinematic dataset of the human body. We hope this dataset will contribute to multiple fields of research and practice, including social neuroscience, psychiatry, computer vision, and biometric and information forensics. Nature Publishing Group UK 2020-09-08 /pmc/articles/PMC7478954/ /pubmed/32901035 http://dx.doi.org/10.1038/s41597-020-00635-7 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Zhang, Mingming Yu, Lu Zhang, Keye Du, Bixuan Zhan, Bin Chen, Shaohua Jiang, Xiuhao Guo, Shuai Zhao, Jiafeng Wang, Yang Wang, Bin Liu, Shenglan Luo, Wenbo Kinematic dataset of actors expressing emotions |
title | Kinematic dataset of actors expressing emotions |
title_full | Kinematic dataset of actors expressing emotions |
title_fullStr | Kinematic dataset of actors expressing emotions |
title_full_unstemmed | Kinematic dataset of actors expressing emotions |
title_short | Kinematic dataset of actors expressing emotions |
title_sort | kinematic dataset of actors expressing emotions |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7478954/ https://www.ncbi.nlm.nih.gov/pubmed/32901035 http://dx.doi.org/10.1038/s41597-020-00635-7 |
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