Face recognition using support vector machines and generalized discriminant analysis
Ivanna K. Timotius, The Christiani Linasari, Iwan Setyawan, Andreas Ardian Febrianto · 2011
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%.