By Jun-Bao Li
Kernel studying Algorithms for Face acceptance covers the framework of kernel dependent face reputation. This booklet discusses the complex kernel studying algorithms and its program on face attractiveness. This e-book additionally makes a speciality of the theoretical deviation, the approach framework and experiments concerning kernel established face acceptance. integrated inside of are algorithms of kernel dependent face acceptance, and in addition the feasibility of the kernel established face acceptance procedure. This booklet presents researchers in development reputation and laptop studying region with complex face reputation equipment and its most recent applications.
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Additional resources for Kernel Learning Algorithms for Face Recognition
IEEE Trans Syst Man Cybern Part B Cybern 35(3):556–562 78. Chen W-S, Yuen PC, Huang J, Dai D-Q (2005) Kernel machine-based one-parameter regularized fisher discriminant method for face recognition. IEEE Trans Syst Man Cybern Part B Cybern 35(4):658–669 79. Liang Y, Li C, Gong W, Pan Y (2007) Uncorrelated linear discriminant analysis based on weighted pairwise fisher criterion. Pattern Recogn 40:3606–3615 80. Zheng Y-J, Yang J, Yang J-Y, Wu X-J (2006) A reformative kernel fisher discriminant algorithm and its application to face recognition.
Baudat G, Anouar F (2000) Generalized discriminant analysis using a kernel approach. Neural Comput 12(10):2385–2404 70. Liang Z, Shi P (2005) Uncorrelated discriminant vectors using a kernel method. Pattern Recogn 38:307–310 71. Liang Z, Shi P (2004) An efficient and effective method to solve kernel fisher discriminant analysis. Neurocomputing 61:485–493 72. Yang J, Frangi AF, Yang J-Y, Zhang D, Jin Z (2005) KPCA plus LDA: a complete kernel fisher discriminant framework for feature extraction and recognition.
Other enhanced algorithms are E(PC)2A  and SVD perturbation , for face recognition with one training image per person. But these algorithms still endure some problem. For example, the procedure of E(PC)2A is divided into two stages: (1) constructing a new image by combining the first-order and second-order projected images and the original image; (2) performing PCA on the newly combined training images. In the second stage, the combined image matrix should be mapped onto a 1D vector in advance in order to perform PCA.