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Facial expression recognition is one of the most active areas of research in computer vision since one of the non-verbal communication methods by which one understands the mood/mental state of a person is the expression of face. Thus, it has been used in various fields such as human-robot interaction, security, computer graphics animation, and ambient assistance. Nevertheless, it remains a challenging task since existing approaches lack generalizability and almost all studies ignore the effects of facial attributes, such as age, on expression recognition even though the research indicates that facial expression manifestation varies with age. Recently, a lot of progress has been made in this topic and great improvements in classification task were achieved with the emergence of deep learning methods. Such approaches have shown how hierarchies of features can be directly learned from original data, thus …
Springer Singapore
Publication date: 
1 Oct 2020
Biblio References: 
Volume: 35 Issue: 5 Pages: 1127-1146
Journal of Computer Science and Technology