Face recognition based on relevance vector machine

Author

Changyuan Liu ; Yan Li ; Xiaojun Bi

Author_Institution

Coll. of Inf. & Commun. Eng., Harbin Eng. Univ., Harbin, China

Volume

2

fYear

2011

fDate

22-24 Aug. 2011

Firstpage

1202

Lastpage

1206

Abstract

A new face recognition approach based on relevance vector machine (RVM) is presented in this paper. Firstly, the wavelet transform is applied to preprocessing face image to reduce the impact of expression change. Then, the principal component analysis (PCA) method is used to extract key features of the processed face image. Finally, the RVM classification model is adopted for identifying. In comparison with the support vector machine (SVM) method, the RVM approach performs well and can obtain more satisfactory results in terms of recognition rates and robustness.

Keywords

face recognition; feature extraction; principal component analysis; support vector machines; wavelet transforms; PCA; SVM; expression change impact reduction; face recognition; feature extraction; principal component analysis; relevance vector machine; support vector machine; wavelet transform; Accuracy; Face; Face recognition; Support vector machines; Testing; Training; Wavelet transforms; face recognition; principal component analysis; relevance vector machine; wavelet transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Strategic Technology (IFOST), 2011 6th International Forum on

Conference_Location

Harbin, Heilongjiang

Print_ISBN

978-1-4577-0398-0

Type

conf

DOI

10.1109/IFOST.2011.6021236

Filename

6021236