51 search results - page 5 / 11 » Multilinear principal component analysis for face recognitio... |
PR
2007
13 years 7 months ago
2007
Feature extraction is among the most important problems in face recognition systems. In this paper, we propose an enhanced kernel discriminant analysis (KDA) algorithm called kern...
FGR
1998
IEEE
14 years 2 hour ago
1998
IEEE
The performance of a local feature based system, using Gabor-filters, and a global template matching based system, using a combination of PCA (Principal Component Analysis) and LD...
JMM2
2008
13 years 7 months ago
2008
Unsupervised or Self-Organized learning algorithms have become very popular for discovery of significant patterns or features in the input data. The three prominent algorithms name...
JCP
2008
13 years 7 months ago
2008
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
ACCV
2007
Springer
14 years 1 months ago
2007
Springer
A novel kernel discriminant transformation (KDT) algorithm based on the concept of canonical differences is presented for automatic face recognition applications. For each individu...