Feature extraction and classification methods of facial expression: a surey

Authors

  • Moe Moe Htay University of Computer Studies, Mandalay (UCSM)

DOI:

https://doi.org/10.11591/csit.v2i1.pp26-32

Keywords:

Expression classification, Facial datasets, Facial features, Feature extraction

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.

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Published

2021-03-01

How to Cite

[1]
Moe Moe Htay, “Feature extraction and classification methods of facial expression: a surey”, Comput Sci Inf Technol, vol. 2, no. 1, pp. 26–32, Mar. 2021.

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Section

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