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Deep Learning and Improved HMM Training Algorithm and Its Analysis in Facial Expression Recognition of Sports Athletes
Facial expressions are an auxiliary embodiment of information conveyed in the communication between people. Facial expressions can not only convey the semantic information that people want to express but also convey the emotional state of the speaker at the same time. But for sports athletes in trai...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8789465/ https://www.ncbi.nlm.nih.gov/pubmed/35087577 http://dx.doi.org/10.1155/2022/1027735 |
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author | Li, Shaolong Bai, Yijun |
author_facet | Li, Shaolong Bai, Yijun |
author_sort | Li, Shaolong |
collection | PubMed |
description | Facial expressions are an auxiliary embodiment of information conveyed in the communication between people. Facial expressions can not only convey the semantic information that people want to express but also convey the emotional state of the speaker at the same time. But for sports athletes in training and competitions, it is usually not convenient to communicate directly. This paper is based on deep learning and an improved HMM training algorithm to study the facial expression recognition of sports athletes. It proposes the construction of deep learning of multilayer neural network, and the rank algorithm is introduced to carry out face recognition experiments with traditional HMM and class-specific HMM methods. The experimental results show that, with the increase of rank value, the class-specific recognition rate is up to 90%, the detection rate is 98% and the time-consuming is 2.5 min, which is better than HMM overall. |
format | Online Article Text |
id | pubmed-8789465 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-87894652022-01-26 Deep Learning and Improved HMM Training Algorithm and Its Analysis in Facial Expression Recognition of Sports Athletes Li, Shaolong Bai, Yijun Comput Intell Neurosci Research Article Facial expressions are an auxiliary embodiment of information conveyed in the communication between people. Facial expressions can not only convey the semantic information that people want to express but also convey the emotional state of the speaker at the same time. But for sports athletes in training and competitions, it is usually not convenient to communicate directly. This paper is based on deep learning and an improved HMM training algorithm to study the facial expression recognition of sports athletes. It proposes the construction of deep learning of multilayer neural network, and the rank algorithm is introduced to carry out face recognition experiments with traditional HMM and class-specific HMM methods. The experimental results show that, with the increase of rank value, the class-specific recognition rate is up to 90%, the detection rate is 98% and the time-consuming is 2.5 min, which is better than HMM overall. Hindawi 2022-01-18 /pmc/articles/PMC8789465/ /pubmed/35087577 http://dx.doi.org/10.1155/2022/1027735 Text en Copyright © 2022 Shaolong Li and Yijun Bai. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Li, Shaolong Bai, Yijun Deep Learning and Improved HMM Training Algorithm and Its Analysis in Facial Expression Recognition of Sports Athletes |
title | Deep Learning and Improved HMM Training Algorithm and Its Analysis in Facial Expression Recognition of Sports Athletes |
title_full | Deep Learning and Improved HMM Training Algorithm and Its Analysis in Facial Expression Recognition of Sports Athletes |
title_fullStr | Deep Learning and Improved HMM Training Algorithm and Its Analysis in Facial Expression Recognition of Sports Athletes |
title_full_unstemmed | Deep Learning and Improved HMM Training Algorithm and Its Analysis in Facial Expression Recognition of Sports Athletes |
title_short | Deep Learning and Improved HMM Training Algorithm and Its Analysis in Facial Expression Recognition of Sports Athletes |
title_sort | deep learning and improved hmm training algorithm and its analysis in facial expression recognition of sports athletes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8789465/ https://www.ncbi.nlm.nih.gov/pubmed/35087577 http://dx.doi.org/10.1155/2022/1027735 |
work_keys_str_mv | AT lishaolong deeplearningandimprovedhmmtrainingalgorithmanditsanalysisinfacialexpressionrecognitionofsportsathletes AT baiyijun deeplearningandimprovedhmmtrainingalgorithmanditsanalysisinfacialexpressionrecognitionofsportsathletes |