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» Diagonal principal component analysis for face recognition
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TIFS
2008
157views more  TIFS 2008»
14 years 11 months ago
Subspace Approximation of Face Recognition Algorithms: An Empirical Study
We present a theory for constructing linear subspace approximations to face-recognition algorithms and empirically demonstrate that a surprisingly diverse set of face-recognition a...
Pranab Mohanty, Sudeep Sarkar, Rangachar Kasturi, ...
PAMI
2000
142views more  PAMI 2000»
14 years 11 months ago
Evolutionary Pursuit and Its Application to Face Recognition
Abstract-- This paper introduces Evolutionary Pursuit (EP) as a novel and adaptive representation method for image encoding and classification. In analogy to projection pursuit met...
Chengjun Liu, Harry Wechsler
ISNN
2009
Springer
15 years 6 months ago
Nonlinear Component Analysis for Large-Scale Data Set Using Fixed-Point Algorithm
Abstract. Nonlinear component analysis is a popular nonlinear feature extraction method. It generally uses eigen-decomposition technique to extract the principal components. But th...
Weiya Shi, Yue-Fei Guo
CVPR
2005
IEEE
16 years 1 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....