Kernel Principal Component Analysis and its Applications in Face Recognition and Active Shape Models

15 Jul 2012Quan Wang

Principal component analysis (PCA) is a popular tool for linear dimensionality reduction and feature extraction. Kernel PCA is the nonlinear form of PCA, which better exploits the complicated spatial structure of high-dimensional features... (read more)

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