Automatic Facial Expression Recognition Using SVM Based on AAMs

Author

Li Wang ; Ruifeng Li ; Ke Wang

Author_Institution

Dept. State Key Lab. of Robot. & Syst., Harbin Inst. of Technol., Harbin, China

Volume

2

fYear

2013

fDate

26-27 Aug. 2013

Firstpage

330

Lastpage

333

Abstract

An automatic facial expression recognition method is proposed to effectively recognize facial expression without any region unrelated to facial region. Support Vector Machine (SVM) is applied to recognize facial expression by Gabor features extracting using Gabor wavelet transformation after separate facial region from images Based on Active Appearance Models (AAMs), which reduce influence of illumination and pose. The feasibility and effectiveness of this system are verified by multiple experiments, and satisfied results are achieved.

Keywords

Gabor filters; face recognition; support vector machines; AAM; Gabor feature extraction; Gabor wavelet on transformation; SVM; active appearance models; automatic facial expression recognition; support vector machine; Active appearance model; Face; Face recognition; Feature extraction; Image recognition; Shape; Support vector machines; Active Appearance Models; Facial expression recognition; Gabor feature; Support Vector Machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2013 5th International Conference on

Conference_Location

Hangzhou

Print_ISBN

978-0-7695-5011-4

Type

conf

DOI

10.1109/IHMSC.2013.226

Filename

6642754