19 search results - page 3 / 4 » Null space versus orthogonal linear discriminant analysis |
ICML
2006
IEEE
14 years 6 months ago
2006
IEEE
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
ICIP
2007
IEEE
13 years 11 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...
AMFG
2005
IEEE
13 years 11 months ago
2005
IEEE
When applied to high-dimensional classification task such as face recognition, linear discriminant analysis (LDA) can extract two kinds of discriminant vectors, those in the null s...
CVPR
2004
IEEE
14 years 7 months ago
2004
IEEE
Linear Discriminant Analysis (LDA) is a popular feature extraction technique for face recognition. However, It often suffers from the small sample size problem when dealing with t...
ICPR
2008
IEEE
14 years 6 months ago
2008
IEEE
We propose a feature selection method that constructs each new feature by analysis of tight error clusters. This is a greedy, time-efficient forward selection algorithm that itera...