Two-stage Recognition and Beyond for Compound Facial Emotion Recognition

Facial emotion recognition is an inherently complex problem due to individual diversity in facial features and racial and cultural differences. Moreover, facial expressions typically reflect the mixture of people's emotional statuses, which can be expressed using compound emotions. Compound fac...

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Detalhes bibliográficos
Autores: Kaminska, Dorota, Aktas, Kadir, Rizhinashvili, Davit, Kuklyanov, Danila, Sham, Abdallah Hussein, Escalera Guerrero, Sergio, Nasrollahi, Kamal, Moeslund, Thomas, Anbarjafari, Gholamreza
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/190923
Acesso em linha:https://hdl.handle.net/2445/190923
Access Level:acceso abierto
Palavra-chave:Reconeixement de formes (Informàtica)
Visió per ordinador
Aprenentatge automàtic
Expressió facial
Pattern recognition systems
Computer vision
Machine learning
Facial expression
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spelling Two-stage Recognition and Beyond for Compound Facial Emotion RecognitionKaminska, DorotaAktas, KadirRizhinashvili, DavitKuklyanov, DanilaSham, Abdallah HusseinEscalera Guerrero, SergioNasrollahi, KamalMoeslund, ThomasAnbarjafari, GholamrezaReconeixement de formes (Informàtica)Visió per ordinadorAprenentatge automàticExpressió facialPattern recognition systemsComputer visionMachine learningFacial expressionFacial emotion recognition is an inherently complex problem due to individual diversity in facial features and racial and cultural differences. Moreover, facial expressions typically reflect the mixture of people's emotional statuses, which can be expressed using compound emotions. Compound facial emotion recognition makes the problem even more difficult because the discrimination between dominant and complementary emotions is usually weak. We have created a database that includes 31,250 facial images with different emotions of 115 subjects whose gender distribution is almost uniform to address compound emotion recognition. In addition, we have organized a competition based on the proposed dataset, held at FG workshop 2020. This paper analyzes the winner's approach a two-stage recognition method (1st stage, coarse recognition; 2nd stage, fine recognition), which enhances the classification of symmetrical emotion labels.MDPI2022202220212022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/2445/190923Articles publicats en revistes (Matemàtiques i Informàtica)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésReproducció del document publicat a: https://doi.org/10.3390/electronics10222847Electronics, 2021, vol. 10, num. 22https://doi.org/10.3390/electronics10222847cc-by (c) Kaminska, Dorota et al., 2021https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:2445/1909232026-05-29T05:05:01Z
dc.title.none.fl_str_mv Two-stage Recognition and Beyond for Compound Facial Emotion Recognition
title Two-stage Recognition and Beyond for Compound Facial Emotion Recognition
spellingShingle Two-stage Recognition and Beyond for Compound Facial Emotion Recognition
Kaminska, Dorota
Reconeixement de formes (Informàtica)
Visió per ordinador
Aprenentatge automàtic
Expressió facial
Pattern recognition systems
Computer vision
Machine learning
Facial expression
title_short Two-stage Recognition and Beyond for Compound Facial Emotion Recognition
title_full Two-stage Recognition and Beyond for Compound Facial Emotion Recognition
title_fullStr Two-stage Recognition and Beyond for Compound Facial Emotion Recognition
title_full_unstemmed Two-stage Recognition and Beyond for Compound Facial Emotion Recognition
title_sort Two-stage Recognition and Beyond for Compound Facial Emotion Recognition
dc.creator.none.fl_str_mv Kaminska, Dorota
Aktas, Kadir
Rizhinashvili, Davit
Kuklyanov, Danila
Sham, Abdallah Hussein
Escalera Guerrero, Sergio
Nasrollahi, Kamal
Moeslund, Thomas
Anbarjafari, Gholamreza
author Kaminska, Dorota
author_facet Kaminska, Dorota
Aktas, Kadir
Rizhinashvili, Davit
Kuklyanov, Danila
Sham, Abdallah Hussein
Escalera Guerrero, Sergio
Nasrollahi, Kamal
Moeslund, Thomas
Anbarjafari, Gholamreza
author_role author
author2 Aktas, Kadir
Rizhinashvili, Davit
Kuklyanov, Danila
Sham, Abdallah Hussein
Escalera Guerrero, Sergio
Nasrollahi, Kamal
Moeslund, Thomas
Anbarjafari, Gholamreza
author2_role author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Reconeixement de formes (Informàtica)
Visió per ordinador
Aprenentatge automàtic
Expressió facial
Pattern recognition systems
Computer vision
Machine learning
Facial expression
topic Reconeixement de formes (Informàtica)
Visió per ordinador
Aprenentatge automàtic
Expressió facial
Pattern recognition systems
Computer vision
Machine learning
Facial expression
description Facial emotion recognition is an inherently complex problem due to individual diversity in facial features and racial and cultural differences. Moreover, facial expressions typically reflect the mixture of people's emotional statuses, which can be expressed using compound emotions. Compound facial emotion recognition makes the problem even more difficult because the discrimination between dominant and complementary emotions is usually weak. We have created a database that includes 31,250 facial images with different emotions of 115 subjects whose gender distribution is almost uniform to address compound emotion recognition. In addition, we have organized a competition based on the proposed dataset, held at FG workshop 2020. This paper analyzes the winner's approach a two-stage recognition method (1st stage, coarse recognition; 2nd stage, fine recognition), which enhances the classification of symmetrical emotion labels.
publishDate 2021
dc.date.none.fl_str_mv 2021
2022
2022
2022
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/190923
url https://hdl.handle.net/2445/190923
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.3390/electronics10222847
Electronics, 2021, vol. 10, num. 22
https://doi.org/10.3390/electronics10222847
dc.rights.none.fl_str_mv cc-by (c) Kaminska, Dorota et al., 2021
https://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc-by (c) Kaminska, Dorota et al., 2021
https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv Articles publicats en revistes (Matemàtiques i Informàtica)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,198674

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