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Title: Two-stage Recognition and Beyond for Compound Facial Emotion Recognition
Author: Kaminska, Dorota
Aktas, Kadir
Rizhinashvili, Davit
Kuklyanov, Danila
Sham, Abdallah Hussein
Escalera Guerrero, Sergio
Nasrollahi, Kamal
Moeslund, Thomas
Anbarjafari, Gholamreza
Keywords: Reconeixement de formes (Informàtica)
Visió per ordinador
Aprenentatge automàtic
Expressió facial
Pattern recognition systems
Computer vision
Machine learning
Facial expression
Issue Date: 19-Nov-2021
Publisher: MDPI
Abstract: 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.
Note: Reproducció del document publicat a:
It is part of: Electronics, 2021, vol. 10, num. 22
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ISSN: 2079-9292
Appears in Collections:Articles publicats en revistes (Matemàtiques i Informàtica)

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