Automatic Facial Expression Recognition Using both Local and Global Information

Author

Xiaoyi Feng ; Baohua Lv ; Zhen Li

Author_Institution

Sch. of Electron. & Inf., Northwestern Polytech. Univ., Xi´an, China

fYear

2006

fDate

7-11 Aug. 2006

Firstpage

1878

Lastpage

1881

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.

Keywords

face recognition; gesture recognition; linear programming; JAFFE database; active appearance model; automatic facial expression recognition; face presentation; facial feature points; feature detection; feature extraction; global texture information; image classification; linear programming; local shape information; local texture information; static images; Active appearance model; Data mining; Face detection; Face recognition; Facial features; Image databases; Image recognition; Principal component analysis; Shape control; Spatial databases; AAM; Feature detection; Global information; Local information;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference, 2006. CCC 2006. Chinese

Conference_Location

Harbin

Print_ISBN

7-81077-802-1

Type

conf

DOI

10.1109/CHICC.2006.280876

Filename

4060424