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Facial Gesture Recognition for Emotion Detection: A Review of Methods and Advancements
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Author(s): Bhuvnesh Kumar (Amritsar Group of Colleges, India), Rajeev Kumar Bedi (Sardar Beant Singh State University, India)and Sunil kumar Gupta (Sardar Beant Singh State University, India)
Copyright: 2023
Pages: 17
Source title:
Handbook of Research on AI-Based Technologies and Applications in the Era of the Metaverse
Source Author(s)/Editor(s): Alex Khang (Global Research Institute of Technology and Engineering, USA), Vrushank Shah (Institute of Technology and Engineering, Indus University, India)and Sita Rani (Department of Computer Science and Engineering, Guru Nanak Dev Engineering College, India)
DOI: 10.4018/978-1-6684-8851-5.ch018
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Abstract
Facial gesture recognition (FGR) is widely regarded as an effective means of displaying and communicating human emotions. This chapter provides a comprehensive review of FGR as a biometric marker technology for detecting facial emotions, encompassing the identification of the six basic facial expressions: happiness, sadness, anger, surprise, fear, and disgust. FGR utilizes advanced algorithms to accurately identify and classify facial emotional states from images, audio, or video captured through various devices such as cameras, laptops, mobile phones, or digital signage systems. Given the importance of accuracy, computational efficiency, and mitigating overfitting, this review also discusses the diverse range of methods and models developed in facial expression recognition research. These advancements aim to enhance the accuracy of the models while minimizing computational resource requirements and addressing overfitting challenges encountered in previous studies.
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