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    CVPR
    2008
    IEEE
    318views Computer Vision» more  CVPR 2008»
    Parameterized Kernel Principal Component Analysis: Theory and applications to supervised and unsupervised image alignment
    15 years 1 months ago
    Parameterized Kernel Principal Component Analysis: Theory and applications to supervised and unsupervised image alignment
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    Parameterized Appearance Models (PAMs) (e.g. eigentracking, active appearance models, morphable models) use Principal Component Analysis (PCA) to model the shape and appearance of...
    Fernando De la Torre, Minh Hoai Nguyen
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