Emotion Detection through Facial Expressions: A Survey of AI-Based Methods

Facial Expression Recognition (FER) is a critical area of research in computer vision and artificial intelligence, enabling machines to interpret human emotions through facial cues. Originating from early facial recognition techniques in the 1960s, FER has evolved with advancements in machine learning and deep learning. It plays a vital role in applications such as human-computer interaction, healthcare, security, and marketing. While traditional approaches relied on 2D image analysis, modern systems leverage 3D modeling and deep learning to enhance accuracy. However, challenges such as cultural variability, occlusion, and real-time processing persist. This study aims to explore advanced FER methodologies to improve robustness and address ethical concerns related to emotion recognition technologies.