A New Face Recognition Method Based on Kernel Fisher Discriminant Analysis
Rui Kong · Journal of Circuits and Systems · 2003
A new face recognition method is proposed. In this method, Kernel Fisher Discriminant Analysis (KFDA) is combined with Linear Support Vector Machine (SVM). KFDA is a new non-linear technique for extracting features. KFDA-based face recognition method is tested and compared with PCA, FDA and ICA-based face recognition methods using the same publicly available ATT database. Experiment results indicate that the performance of KFDA-based face recognition method is superior to the others.