Abstract
Facial emotion recognition plays a vital role in computational empathy enabling the nature and effectiveness of human-machine interaction. Although facial emotion has received much attention over the last years as the number of applications has increased, it remains a complicated issue due to facial features and ethnic and cultural differences in facial expressions. This short survey reviews the updated deep learning techniques used for facial emotion recognition. It explores and classifies deep learning models and datasets used for facial emotion recognition. The outcome of the reviews indicates that facial emotion recognition limits complexity and accuracy. This paper also points out the research directions for future work.
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Alharbi, K., Semwal, S. (2023). Computational Empathy Using Facial Emotion Recognition: An Update. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2023, Volume 4. FTC 2023. Lecture Notes in Networks and Systems, vol 816. Springer, Cham. https://doi.org/10.1007/978-3-031-47448-4_7
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DOI: https://doi.org/10.1007/978-3-031-47448-4_7
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