Facial expression recognition based on feature point vector and texture deformation energy parameters

Ji Zheng Yi, Xia Mao, Ishizuka Mitsuru, Yu Li Xue

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Facial expression recognition is a popular and difficult research field in human-computer interaction. In order to remove effectively the differences in expression feature caused by individual differences, this paper firstly presents the feature point distance ratio coefficient based on feature point vector, and then gives the concept of texture deformation energy parameters. Finally, merges previously mentioned two parts to form a new expression feature for facial expression recognition. The proposed method is tested in the Cohn-Kanade database and the BHU facial expression database, and the experimental results show the recognition rates of the proposed method comparing with the existing ones increased by 4.5% and 3.9%.

Original languageEnglish
Pages (from-to)2403-2410
Number of pages8
JournalDianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology
Volume35
Issue number10
DOIs
Publication statusPublished - 2013 Oct
Externally publishedYes

Keywords

  • Facial expression recognition
  • Feature point vector
  • Radial basis function neural network
  • Texture deformation energy parameters

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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