Feature extraction and classification methods of facial expression: a surey

Moe Moe Htay

Abstract


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.


Keywords


Facial features; Feature extraction; Expression classification; Facial datasets



DOI: https://doi.org/10.11591/APTIKOM.J.CSIT.145

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Copyright (c) 2020 APTIKOM Journal on Computer Science and Information Technologies

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ISSN: 2528-2417, e-ISSN: 2528-2425

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Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.