Automatic facial expression recognition using both local and global information

Xiaoyi Feng, Baohua Lv, Zhen Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

A novel approach to automatic facial expression recognition from static images is proposed in this paper. First, Active Appearance Model (AAM) is used to locate facial feature points automatically. Then, both local texture information and local shape information in these points are extracted and are combined with global texture information for face presentation. Finally, the Linear Programming (LP) technique is used for classification. Experimental results demonstrate an average recognition accuracy of 83.6% on the JAFFE database, which shows that the proposed method is promising.

Original languageEnglish
Title of host publication2006 Chinese Control Conference Proceedings, CCC 2006
PublisherIEEE Computer Society
Pages1878-1881
Number of pages4
ISBN (Print)7810778021, 9787810778022
DOIs
StatePublished - 2006
Event25th Chinese Control Conference, CCC 2006 - Harbin, China
Duration: 7 Aug 200611 Aug 2006

Publication series

Name2006 Chinese Control Conference Proceedings, CCC 2006

Conference

Conference25th Chinese Control Conference, CCC 2006
Country/TerritoryChina
CityHarbin
Period7/08/0611/08/06

Keywords

  • AAM
  • Feature detection
  • Global information
  • Local information

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