Open AccessFeature extraction and classification methods of facial expression: a survey
Author(s) -
Moe Moe Htay
Publication year - 2021
Publication title -
computer science and information technologies
Language(s) - English
Resource type - Journals
eISSN - 2722-323X
pISSN - 2722-3221
DOI - 10.11591/csit.v2i1.p26-32
Subject(s) - facial expression , feature extraction , computer science , expression (computer science) , face (sociological concept) , artificial intelligence , feature (linguistics) , pattern recognition (psychology) , facial recognition system , face detection , three dimensional face recognition , affect (linguistics) , computer vision , psychology , communication , social science , linguistics , philosophy , sociology , programming language
Facial Expression is a significant role in affective computing and one of the non-verbal communication for human computer interaction. Automatic recognition of human affects has become more challenging and interesting problem in recent years. Facial Expression is the significant features to recognize the human emotion in human daily life. Facial Expression Recognition System (FERS) can be developed for the application of human affect analysis, health care assessment, distance learning, driver fatigue detection and human computer interaction. Basically, there are three main components to recognize the human facial expression. They are face or face’s components detection, feature extraction of face image, classification of expression. The study proposed the methods of feature extraction and classification for FER.