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ICCV
1999
IEEE

Principal Manifolds and Bayesian Subspaces for Visual Recognition

9 years 8 months ago
Principal Manifolds and Bayesian Subspaces for Visual Recognition
We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Three techniques: Principal Component Analysis (PCA), Independent Component Analysis (ICA) and Nonlinear PCA (NLPCA) are examined and tested in a visual recognition experiment using a large gallery of facial images from the
Baback Moghaddam
Added 03 Aug 2010
Updated 03 Aug 2010
Type Conference
Year 1999
Where ICCV
Authors Baback Moghaddam
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