315 search results - page 31 / 63 » Linear Regression for Face Recognition |
AUSAI
2005
Springer
15 years 5 months ago
2005
Springer
Abstract. Principal Component Analysis (PCA) plus Linear Discriminant Analysis (LDA) (PCA+LDA) and LDA/QR are both two-stage methods that deal with the small sample size (SSS) prob...
ICPR
2004
IEEE
16 years 27 days ago
2004
IEEE
Most face recognition approaches either assume constant lighting condition or standard facial expressions, thus cannot deal with both kinds of variations simultaneously. This prob...
107
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CVPR
2005
IEEE
15 years 11 months ago
2005
IEEE
A novel framework called 2D Fisher Discriminant Analysis
(2D-FDA) is proposed to deal with the Small Sample
Size (SSS) problem in conventional One-Dimensional Linear
Discriminan...
114
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FGR
2008
IEEE
15 years 6 months ago
2008
IEEE
Partial occlusions in face images pose a great problem for most face recognition algorithms. Several solutions to this problem have been proposed over the years – ranging from d...
ECCV
2010
Springer
15 years 5 months ago
2010
Springer
Abstract. By coding the input testing image as a sparse linear combination of the training samples via l1-norm minimization, sparse representation based classification (SRC) has b...