Facial Emotion Detection: A Comprehensive Survey

Facial emotion is most important in human aspects as it communicates in a nonverbal way. This non-verbal form of expression significantly enhances social interactions, enabling individuals to comprehend and respond to each other's feelings Facial emotion detection is a process in which identifying and recognizing human facial emotions based on their expressions is necessary. Analyzing facial features like eyes, mouth, and eyebrows to identify emotions such as happiness, sadness, anger, and surprise, is crucial in making a better prediction. Moreover, facial expressions are crucial in various professional fields like law, knowing whether a person is dishonest or not, psychology where recognizing the emotion of an individual is necessary for analyzing the mental well-being of a person, additionally in the Security and Surveillance domain where identifying suspicious behavior or emotional states of a person in public spaces which helps in contributing to the improvement of public safety measures. There are many Machine Learning Algorithms like Support Vector Machines, Decision Trees, and Random Forests which are initially used in identifying emotions based on facial expressions. But Compared to Traditional Facial Recognition using Machine Learning Algorithms, Deep learning models like Convolutional Neural Networks (CNN) have shown much better accuracy because they can be able to localize complex features and Hierarchical Feature Representation helps in segmenting the features into low and high levels this enables the model to identify minute things. The primary objective of this paper is to make a survey on ML and deep learning algorithms and their significance in Facial emotion detection.