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Article type: Research Article
Authors: Masson, Audreya; b; * | Cazenave, Guillaumeb | Trombini, Julienb | Batt, Martinea
Affiliations: [a] Interpsy – GRC, University of Lorraine, France. E-mails: audrey.masson@two-i.fr, martine.batt@univ-lorraine.fr | [b] Two-I, France. E-mails: guillaume.cazenave@two-i.fr, julien.trombini@two-i.fr
Correspondence: [*] Corresponding author. E-mail: audrey.masson@two-i.fr.
Abstract: In recent years, due to its great economic and social potential, the recognition of facial expressions linked to emotions has become one of the most flourishing applications in the field of artificial intelligence, and has been the subject of many developments. However, despite significant progress, this field is still subject to many theoretical debates and technical challenges. It therefore seems important to make a general inventory of the different lines of research and to present a synthesis of recent results in this field. To this end, we have carried out a systematic review of the literature according to the guidelines of the PRISMA method. A search of 13 documentary databases identified a total of 220 references over the period 2014–2019. After a global presentation of the current systems and their performance, we grouped and analyzed the selected articles in the light of the main problems encountered in the field of automated facial expression recognition. The conclusion of this review highlights the strengths, limitations and main directions for future research in this field.
Keywords: Artificial intelligence, affective computing, facial expression, AFER, emotion theories
DOI: 10.3233/AIC-200631
Journal: AI Communications, vol. 33, no. 3-6, pp. 113-138, 2020
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