Facial Emotion Recognition: A Review on State-of-the-art Techniques

Emotions are fundamental to human communication and understanding them through facial expressions is essential for developing emotionally intelligent systems. Emotions play a pivotal role in human communication and influence decision-making processes. Accurate Facial Emotion Recognition (FER) is crucial for applications in various domains, including healthcare, marketing, and human-computer interaction. Traditional FER approaches often relied on handcrafted features, while modern methods leverage deep neural networks to automatically extract discriminative features from facial images. However, challenges related to real-world applications, ethical concerns, and cultural nuances remain. Addressing these challenges is crucial for the continued development and deployment of FER systems in various domains. This paper provides an overview of the key aspects, challenges, and advancements in FER. This paper also provides information about the different datasets used for different algorithms and gives a relative analysis of the recent methods in the field of facial emotion recognition.