Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/190923
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: https://doi.org/10.3390/electronics10222847 |
It is part of: | Electronics, 2021, vol. 10, num. 22 |
URI: | http://hdl.handle.net/2445/190923 |
Related resource: | https://doi.org/10.3390/electronics10222847 |
ISSN: | 2079-9292 |
Appears in Collections: | Articles publicats en revistes (Matemàtiques i Informàtica) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
715920.pdf | 8.18 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License