Survey of intelligent classifier approaches for facial expression recognition

Amir Jamshid Nezhad, Md. Jan Nordin

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In recent years understanding of emotions is a basic requirement in the development of human computer interaction (HCI) systems. Emotion is recognized based on the interpreting of facial expressions, body motions and verbal communications. However, facial expression recognition is considered more than the other signs and effects, because human face is the most changeable part of body which is affected when the emotion is occurred. Six basic expressions include "happiness", "anger", "sadness", "fear", "surprise", and "disgust" can recognize by the facial expression recognition systems. The purpose of this paper is survey of current researches and methods on the facial expression recognition systems. Feature extraction as well as classification methods for clustering the emotions are discussed to consider their accuracy and the processing time. Then, based on the advantages and disadvantages of the current methods a hybrid Genetic-Fuzzy classifier model is proposed.

Original languageEnglish
Pages (from-to)66-71
Number of pages6
JournalInternational Review on Computers and Software
Volume6
Issue number1
Publication statusPublished - Jan 2011
Externally publishedYes

Fingerprint

Human computer interaction
Feature extraction
Classifiers
Communication
Processing

Keywords

  • Classifier
  • Facial expression recognition
  • Fuzzy logic
  • Genetic algorithm

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Survey of intelligent classifier approaches for facial expression recognition. / Nezhad, Amir Jamshid; Nordin, Md. Jan.

In: International Review on Computers and Software, Vol. 6, No. 1, 01.2011, p. 66-71.

Research output: Contribution to journalArticle

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