An initial study of feature extraction’s methods in facial expression recognition

Facial Expression Recognition is a sub-branch of Affective Computing that specializes in extracting human emotions and facial features from visual input (images and videos) and tagging them to specific emotion hierarchies. The difficulty of this task lies not only in the subjectivity of distinguishing between human emotional states but, also in the diversity of the human race and culture that influences how we humans perceive sentiments. This article aims to tackle this challenge through two distinct methods of image processing, meaning automatic, Artificial Intelligence (AI) driven feature extraction and manual feature extraction through classical approaches and compare the performance of each of them afterwards. Our conclusion is, that both methods yield noteworthy results, and each specializes in a different context.