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Advancements in Facial Expression Recognition Using Machine and Deep Learning Techniques

Advancements in Facial Expression Recognition Using Machine and Deep Learning Techniques

Shivani Singh, Jay Kumar Pandey, Mritunjay Rai, Abhishek Kumar Saxena
Copyright: © 2024 |Pages: 18
ISBN13: 9798369341438|ISBN13 Softcover: 9798369353080|EISBN13: 9798369341445
DOI: 10.4018/979-8-3693-4143-8.ch007
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MLA

Singh, Shivani, et al. "Advancements in Facial Expression Recognition Using Machine and Deep Learning Techniques." Machine and Deep Learning Techniques for Emotion Detection, edited by Mritunjay Rai and Jay Kumar Pandey, IGI Global, 2024, pp. 149-166. https://doi.org/10.4018/979-8-3693-4143-8.ch007

APA

Singh, S., Pandey, J. K., Rai, M., & Saxena, A. K. (2024). Advancements in Facial Expression Recognition Using Machine and Deep Learning Techniques. In M. Rai & J. Pandey (Eds.), Machine and Deep Learning Techniques for Emotion Detection (pp. 149-166). IGI Global. https://doi.org/10.4018/979-8-3693-4143-8.ch007

Chicago

Singh, Shivani, et al. "Advancements in Facial Expression Recognition Using Machine and Deep Learning Techniques." In Machine and Deep Learning Techniques for Emotion Detection, edited by Mritunjay Rai and Jay Kumar Pandey, 149-166. Hershey, PA: IGI Global, 2024. https://doi.org/10.4018/979-8-3693-4143-8.ch007

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Abstract

In the field of computer vision, facial expression recognition is an emerging field that looks at visual face data to try and understand human emotions. Facial expression detection and recognition has been popular recently in the research field. The literature is compiled from several credible studies that have been released in the last 10 years. In the recent years, the artificial intelligence has evolved a lot along with which there has been rise in experimenting with various methodologies for facial expression recognition, which has given promising results in accurately identifying and recognizing facial emotions from input modalities like images, text, facial expressions, and physiological signals. However, accurate analysis of basic emotions like anger, happiness, sadness, and fear remains a challenge. This chapter provides valuable insights for researchers interested in advancing facial emotion recognition using machine learning and deep learning techniques.

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