Multiple Face Model of Hybrid Fourier Feature for Large Face Image Set

The face recognition system based on the only single classifier considering the restricted information can not guarantee the generality and superiority of performances in a real situation. To challenge such problems, we propose the hybrid Fourier features extracted from different frequency bands and multiple face models. The hybrid Fourier feature comprises three different Fourier domains; merged real and imaginary components, Fourier spectrum and phase angle. When deriving Fourier features from three Fourier domains, we define three different frequency bandwidths, so that additional complementary features can be obtained. After this, they are individually classified by Linear Discriminant Analysis. This approach makes possible analyzing a face image from the various viewpoints to recognize identities. Moreover, we propose multiple face models based on different eye positions with a same image size, and it contributes to increasing the performance of the proposed system. We evaluated ...

• Type: Conference
• Year: 2006
• Where: CVPR
• Authors: Wonjun Hwang, Gyu-tae Park, Jong Ha Lee, Seok-Cheol Kee
• Keywords: Computer Vision, CVPR 2006, Fourier Features, Hybrid Fourier Feature, Multiple Face Models