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 facial e...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/10/22/2847 |
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| author | Dorota Kamińska Kadir Aktas Davit Rizhinashvili Danila Kuklyanov Abdallah Hussein Sham Sergio Escalera Kamal Nasrollahi Thomas B. Moeslund Gholamreza Anbarjafari |
| author_facet | Dorota Kamińska Kadir Aktas Davit Rizhinashvili Danila Kuklyanov Abdallah Hussein Sham Sergio Escalera Kamal Nasrollahi Thomas B. Moeslund Gholamreza Anbarjafari |
| author_sort | Dorota Kamińska |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T05:32:51Z |
| format | Article |
| id | doaj.art-cb153d34f43348b1b5ebe8fd3df0ce69 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-10T05:32:51Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-cb153d34f43348b1b5ebe8fd3df0ce692023-11-22T23:07:58ZengMDPI AGElectronics2079-92922021-11-011022284710.3390/electronics10222847Two-Stage Recognition and beyond for Compound Facial Emotion RecognitionDorota Kamińska0Kadir Aktas1Davit Rizhinashvili2Danila Kuklyanov3Abdallah Hussein Sham4Sergio Escalera5Kamal Nasrollahi6Thomas B. Moeslund7Gholamreza Anbarjafari8Institute of Mechatronics and Information Systems, Lodz University of Technology, 90924 Lodz, PolandiCV Lab, University of Tartu, 50090 Tartu, EstoniaiCV Lab, University of Tartu, 50090 Tartu, EstoniaiCV Lab, University of Tartu, 50090 Tartu, EstoniaEnactive Virtuality Lab, University of Tallinn, 19086 Tallinn, EstoniaComputer Vision Center, 08193 Barcelona, SpainVisual Analysis and Perception Lab, University of Aalborg, 9220 Aalborg, DenmarkVisual Analysis and Perception Lab, University of Aalborg, 9220 Aalborg, DenmarkiCV Lab, University of Tartu, 50090 Tartu, EstoniaFacial 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.https://www.mdpi.com/2079-9292/10/22/2847compound emotion recognitionfacial expression recognitiondominant and complementary emotion recognitiondeep learning |
| spellingShingle | Dorota Kamińska Kadir Aktas Davit Rizhinashvili Danila Kuklyanov Abdallah Hussein Sham Sergio Escalera Kamal Nasrollahi Thomas B. Moeslund Gholamreza Anbarjafari Two-Stage Recognition and beyond for Compound Facial Emotion Recognition Electronics compound emotion recognition facial expression recognition dominant and complementary emotion recognition deep learning |
| title | 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_short | Two-Stage Recognition and beyond for Compound Facial Emotion Recognition |
| title_sort | two stage recognition and beyond for compound facial emotion recognition |
| topic | compound emotion recognition facial expression recognition dominant and complementary emotion recognition deep learning |
| url | https://www.mdpi.com/2079-9292/10/22/2847 |
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