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» Nonparametric Subspace Analysis for Face Recognition
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CVPR
2005
IEEE
14 years 9 months ago
Representational Oriented Component Analysis (ROCA) for Face Recognition with One Sample Image per Training Class
Subspace methods such as PCA, LDA, ICA have become a standard tool to perform visual learning and recognition. In this paper we propose Representational Oriented Component Analysi...
Fernando De la Torre, Ralph Gross, Simon Baker, B....
CVPR
1998
IEEE
14 years 9 months ago
Probabilistic Reasoning Models for Face Recognition
We introduce in this paper two probabilistic reasoning models (PRM-1 and PRM-2) which combine the Principal Component Analysis (PCA) technique and the Bayes classifier and show th...
Chengjun Liu, Harry Wechsler
ICCV
2009
IEEE
15 years 13 days ago
Subspace Constrained Mean-Shift
Deformable model fitting has been actively pursued in the computer vision community for over a decade. As a result, numerous approaches have been proposed with varying degrees of...
Jason M. Saragih, Simon Lucey, Jeffrey F. Cohn
CVPR
2004
IEEE
14 years 9 months ago
Dual-Space Linear Discriminant Analysis for Face Recognition
Linear Discriminant Analysis (LDA) is popular feature extraction technique for face recognition. However, it often suffers from the small sample size problem when dealing with the...
Xiaogang Wang, Xiaoou Tang
ICIP
2006
IEEE
14 years 9 months ago
Fusion of Visible and Infrared Images using Empirical Mode Decomposition to Improve Face Recognition
In this effort, we propose a new image fusion technique, utilizing Empirical Mode Decomposition (EMD), for improved face recognition. EMD is a non-parametric datadriven analysis t...
Harishwaran Hariharan, Andreas Koschan, Besma R. A...