A Study of Various Algorithms for Facial Expression Recognition: A Review

Facial Expression Recognition (FER) is an important thrust area in the field of artificial intelligence and computer vision. The features of various faces and their characteristics are analyzed to achieve the concept of FER. The facial characteristics are retrieved using an automated face detection method which helps to identify the emotions of a person. This study examines in-depth FER investigations using several techniques, such as template, appearance, knowledge-based and feature-based approaches, coupled with a variety of algorithms such as viola jones, Faster RCNN, SSD, MTCNN and Face landmark Detection. These techniques are used to classify the different emotions of the human face such as happiness, wrath, sorrow, disgust, fear, neutrality, surprise and disdain. Moreover, research works based on deep learning based FER models are also examined.