Facial emotion recognition through artificial intelligence
Main Author: | |
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Publication Date: | 2024 |
Other Authors: | , , , |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | https://hdl.handle.net/11328/5367 https://doi.org/10.3389/fcomp.2024.1359471 |
Summary: | This paper introduces a study employing artificial intelligence (AI) to utilize computer vision algorithms for detecting human emotions in video content during user interactions with diverse visual stimuli. The research aims to unveil the creation of software capable of emotion detection by leveraging AI algorithms and image processing pipelines to identify users' facial expressions. The process involves assessing users through images and facilitating the implementation of computer vision algorithms aligned with psychological theories defining emotions and their recognizable features. The study demonstrates the feasibility of emotion recognition through convolutional neural networks (CNN) and software development and training based on facial expressions. The results highlight successful emotion identification; however, precision improvement necessitates further training for contexts with more diverse images and additional algorithms to distinguish closely related emotional patterns. The discussion and conclusions emphasize the potential of A.I. and computer vision algorithms in emotion detection, providing insights into software development, ongoing training, and the evolving landscape of emotion recognition technology. Further training is necessary for contexts with more diverse images, alongside additional algorithms that can effectively distinguish between facial expressions depicting closely related emotional patterns, enhancing certainty and accuracy. |
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Facial emotion recognition through artificial intelligenceFacial emotionRecognitionAIConvolutional neural networkImagesThis paper introduces a study employing artificial intelligence (AI) to utilize computer vision algorithms for detecting human emotions in video content during user interactions with diverse visual stimuli. The research aims to unveil the creation of software capable of emotion detection by leveraging AI algorithms and image processing pipelines to identify users' facial expressions. The process involves assessing users through images and facilitating the implementation of computer vision algorithms aligned with psychological theories defining emotions and their recognizable features. The study demonstrates the feasibility of emotion recognition through convolutional neural networks (CNN) and software development and training based on facial expressions. The results highlight successful emotion identification; however, precision improvement necessitates further training for contexts with more diverse images and additional algorithms to distinguish closely related emotional patterns. The discussion and conclusions emphasize the potential of A.I. and computer vision algorithms in emotion detection, providing insights into software development, ongoing training, and the evolving landscape of emotion recognition technology. Further training is necessary for contexts with more diverse images, alongside additional algorithms that can effectively distinguish between facial expressions depicting closely related emotional patterns, enhancing certainty and accuracy.Frontiers Media2024-02-05T17:16:48Z2024-02-052024-01-31T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfBallesteros, J. A., Ramírez V., G. M., Moreira, F., Solano, A., & Pelaez, C. A. (2024). Facial emotion recognition through artificial intelligence. Frontiers in Computer Science, 6(Published online: 31 january 2024), 1-14. https://doi.org/10.3389/fcomp.2024.1359471. Repositório Institucional UPT. https://hdl.handle.net/11328/5367https://hdl.handle.net/11328/5367Ballesteros, J. A., Ramírez V., G. M., Moreira, F., Solano, A., & Pelaez, C. A. (2024). Facial emotion recognition through artificial intelligence. Frontiers in Computer Science, 6(Published online: 31 january 2024), 1-14. https://doi.org/10.3389/fcomp.2024.1359471. Repositório Institucional UPT. https://hdl.handle.net/11328/5367https://hdl.handle.net/11328/5367https://doi.org/10.3389/fcomp.2024.1359471eng2624-9898https://www.frontiersin.org/articles/10.3389/fcomp.2024.1359471/fullhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessBallesteros, Jesús A.Ramírez V., Gabriel M.Solano, AndrésPelaez, Carlos A.Moreira, Fernandoreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-04-24T02:05:40Zoai:repositorio.upt.pt:11328/5367Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T19:33:04.106508Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Facial emotion recognition through artificial intelligence |
title |
Facial emotion recognition through artificial intelligence |
spellingShingle |
Facial emotion recognition through artificial intelligence Ballesteros, Jesús A. Facial emotion Recognition AI Convolutional neural network Images |
title_short |
Facial emotion recognition through artificial intelligence |
title_full |
Facial emotion recognition through artificial intelligence |
title_fullStr |
Facial emotion recognition through artificial intelligence |
title_full_unstemmed |
Facial emotion recognition through artificial intelligence |
title_sort |
Facial emotion recognition through artificial intelligence |
author |
Ballesteros, Jesús A. |
author_facet |
Ballesteros, Jesús A. Ramírez V., Gabriel M. Solano, Andrés Pelaez, Carlos A. Moreira, Fernando |
author_role |
author |
author2 |
Ramírez V., Gabriel M. Solano, Andrés Pelaez, Carlos A. Moreira, Fernando |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Ballesteros, Jesús A. Ramírez V., Gabriel M. Solano, Andrés Pelaez, Carlos A. Moreira, Fernando |
dc.subject.por.fl_str_mv |
Facial emotion Recognition AI Convolutional neural network Images |
topic |
Facial emotion Recognition AI Convolutional neural network Images |
description |
This paper introduces a study employing artificial intelligence (AI) to utilize computer vision algorithms for detecting human emotions in video content during user interactions with diverse visual stimuli. The research aims to unveil the creation of software capable of emotion detection by leveraging AI algorithms and image processing pipelines to identify users' facial expressions. The process involves assessing users through images and facilitating the implementation of computer vision algorithms aligned with psychological theories defining emotions and their recognizable features. The study demonstrates the feasibility of emotion recognition through convolutional neural networks (CNN) and software development and training based on facial expressions. The results highlight successful emotion identification; however, precision improvement necessitates further training for contexts with more diverse images and additional algorithms to distinguish closely related emotional patterns. The discussion and conclusions emphasize the potential of A.I. and computer vision algorithms in emotion detection, providing insights into software development, ongoing training, and the evolving landscape of emotion recognition technology. Further training is necessary for contexts with more diverse images, alongside additional algorithms that can effectively distinguish between facial expressions depicting closely related emotional patterns, enhancing certainty and accuracy. |
publishDate |
2024 |
dc.date.none.fl_str_mv |
2024-02-05T17:16:48Z 2024-02-05 2024-01-31T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
Ballesteros, J. A., Ramírez V., G. M., Moreira, F., Solano, A., & Pelaez, C. A. (2024). Facial emotion recognition through artificial intelligence. Frontiers in Computer Science, 6(Published online: 31 january 2024), 1-14. https://doi.org/10.3389/fcomp.2024.1359471. Repositório Institucional UPT. https://hdl.handle.net/11328/5367 https://hdl.handle.net/11328/5367 Ballesteros, J. A., Ramírez V., G. M., Moreira, F., Solano, A., & Pelaez, C. A. (2024). Facial emotion recognition through artificial intelligence. Frontiers in Computer Science, 6(Published online: 31 january 2024), 1-14. https://doi.org/10.3389/fcomp.2024.1359471. Repositório Institucional UPT. https://hdl.handle.net/11328/5367 https://hdl.handle.net/11328/5367 https://doi.org/10.3389/fcomp.2024.1359471 |
identifier_str_mv |
Ballesteros, J. A., Ramírez V., G. M., Moreira, F., Solano, A., & Pelaez, C. A. (2024). Facial emotion recognition through artificial intelligence. Frontiers in Computer Science, 6(Published online: 31 january 2024), 1-14. https://doi.org/10.3389/fcomp.2024.1359471. Repositório Institucional UPT. https://hdl.handle.net/11328/5367 |
url |
https://hdl.handle.net/11328/5367 https://doi.org/10.3389/fcomp.2024.1359471 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2624-9898 https://www.frontiersin.org/articles/10.3389/fcomp.2024.1359471/full |
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http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
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http://creativecommons.org/licenses/by/4.0/ |
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openAccess |
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Frontiers Media |
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Frontiers Media |
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