EMD Based Face Gender Discrimination

A novel method for face gender discrimination was proposed. The method got 27 intrinsic mode functions (IMFs) by calculating empirical mode decomposition (EMD) for 3 mean faces. For face gender feature extraction, the method used these IMFs as projection vectors. Finally, kernel Fisher discriminant analysis (KFDA) and support vector machine (SVM) were used for classification, respectively. With the same performance for face gender discrimination, computational results show that the efficiency of EMD+KFDA method is more than 3.7 times as that of direct KFDA method, and the EMD+SVM method is at least 1.5 times faster than the PCA + SVM method