334 search results - page 3 / 67 » Diagonal principal component analysis for face recognition |
CVPR
2006
IEEE
14 years 7 months ago
2006
IEEE
Linear Discriminant Analysis (LDA) is a well-known and important tool in pattern recognition with potential applications in many areas of research. The most famous and used formul...
ISNN
2004
Springer
13 years 11 months ago
2004
Springer
Abstract. Principal Component Analysis (PCA) is a feature extraction approach directly based on a whole vector pattern and acquires a set of projections that can realize the best r...
JACM
2011
12 years 8 months ago
2011
This paper is about a curious phenomenon. Suppose we have a data matrix, which is the superposition of a low-rank component and a sparse component. Can we recover each component i...
ICIP
2007
IEEE
13 years 12 months ago
2007
IEEE
Gait has received much attention from researchers in the vision field due to its utility in walker identification. One of the key issues in gait recognition is how to extract di...
PAMI
2008
13 years 5 months ago
2008
In data-analysis problems with a large number of dimension, principal component analysis based on L2-norm (L2PCA) is one of the most popular methods, but L2-PCA is sensitive to out...