Recognizing Faces using Kernel Eigenfaces and Support Vector Machines.
In face recognition, principal component analysis (PCA) is often used to extract a low dimensional face representation based on the eigenvector of the face image autocorrelation matrix. Kernel Principal Component Analysis (Kernel PCA) has recently been proposed as a non linear extension of CPA. Whil...
| Publicat a: | Philippine Computing Journal 1, 1 (2006). |
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| Autor principal: | |
| Format: | Article |
| Idioma: | English |