Age-Group Classification of Facial Images

Author

Li Liu ; Jianming Liu ; Jun Cheng

Author_Institution

Electron. Eng. & Autom. Dept., Guilin Univ. of Electron. Technol., Guilin, China

Volume

1

fYear

2012

fDate

12-15 Dec. 2012

Firstpage

693

Lastpage

696

Abstract

This paper presents the age-group classification based on facial images. We perform age-group classification by dividing ages into five age groups according to the incremental regulation of age. Features are extracted from face images through Active Appearance Model (AAM), which describe the shape and gray value variation of face images. Principle Component Analysis (PCA) is adopted to reduce the dimensions and Support Vector Machine (SVM) classifier with Gaussian Radian Basis Function (RBF) kernel is trained. Experimental results demonstrate that AAM can improve the performance of age estimation.

Keywords

Gaussian processes; face recognition; image classification; image colour analysis; principal component analysis; radial basis function networks; support vector machines; AAM; Gaussian radian basis function kernel; PCA; RBF; SVM; active appearance model; age estimation; age-group classification; facial images; gray value variation; principle component analysis; shape variation; support vector machine classifier; Machine learning; AAM; RBF; SVM; age-group classification;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Applications (ICMLA), 2012 11th International Conference on

Conference_Location

Boca Raton, FL

Print_ISBN

978-1-4673-4651-1

Type

conf

DOI

10.1109/ICMLA.2012.129

Filename

6406650