Face recognition using support vector machines and generalized discriminant analysis

Author

Timotius, Ivanna K. ; Linasari, The Christiani ; Setyawan, Iwan ; Febrianto, Andreas A.

Author_Institution

Dept. of Electron. Eng., Satya Wacana Christian Univ., Salatiga, Indonesia

fYear

2011

fDate

20-21 Oct. 2011

Firstpage

8

Lastpage

10

Abstract

Face recognition by machines has various important applications in our daily life. However, the task to teach machine to recognize face images has been a very challenging task. This paper presents face recognition by combining Generalized Discriminant Analysis (GDA) as a feature extractor and Support Vector Machines (SVM) as a classifier. Our experiment showed that the performance of combining these two methods as a face image classifier is better than by only using SVM. The accuracy of combined method is above 85%.

Keywords

face recognition; feature extraction; image classification; learning (artificial intelligence); support vector machines; SVM; face image classifier; face recognition; feature extractor; generalized discriminant analysis; support vector machines; Accuracy; Face; Face recognition; Feature extraction; Kernel; Support vector machines; Vectors; Face Recognition; Generalized Discriminant Analysis; Support Vector Machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Telecommunication Systems, Services, and Applications (TSSA), 2011 6th International Conference on

Conference_Location

Bali

Print_ISBN

978-1-4577-1441-2

Type

conf

DOI

10.1109/TSSA.2011.6095397

Filename

6095397