A study of dimension reduction of Gabor features from different facial expressions

Rosdiyana Samad, Hideyuki Sawada

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Facial expressions are an important channel of nonverbal communication. Currently, many facial expression analysis or recognition systems have been proposed. In this paper, a study of dimension reduction of Gabor features from different facial expressions is presented. Principle Component Analysis (PCA) is used as dimension reduction method. The experiment is conducted by using samples of face image for eight subjects. There are six facial expressions; anger, fear, happy, neutral, sadness and surprise are used in this study. In this experiment, we use different poses and head postures of each subject. Experiment results demonstrated the reduced dimensions of Gabor features could be effectively used in the next processing for recognizing facial expressions.

Original languageEnglish
Title of host publicationProceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10
Pages610-613
Number of pages4
Publication statusPublished - 2010 Dec 1
Externally publishedYes
Event15th International Symposium on Artificial Life and Robotics, AROB '10 - Beppu, Oita, Japan
Duration: 2010 Feb 42010 Feb 6

Publication series

NameProceedings of the 15th International Symposium on Artificial Life and Robotics, AROB 15th'10

Other

Other15th International Symposium on Artificial Life and Robotics, AROB '10
CountryJapan
CityBeppu, Oita
Period10/2/410/2/6

Keywords

  • Dimension reduction
  • Facial expression
  • Gabor features
  • PCA

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction

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