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NPL
2006
130views more  NPL 2006»
15 years 6 months ago
A Fast Feature-based Dimension Reduction Algorithm for Kernel Classifiers
This paper presents a novel dimension reduction algorithm for kernel based classification. In the feature space, the proposed algorithm maximizes the ratio of the squared between-c...
Senjian An, Wanquan Liu, Svetha Venkatesh, Ronny T...
ICCV
2007
IEEE
16 years 8 months ago
Spectral Regression for Efficient Regularized Subspace Learning
Subspace learning based face recognition methods have attracted considerable interests in recent years, including Principal Component Analysis (PCA), Linear Discriminant Analysis ...
Deng Cai, Xiaofei He, Jiawei Han
AUSAI
2005
Springer
15 years 12 months ago
New Feature Extraction Approaches for Face Recognition
All the traditional PCA-based and LDA-based methods are based on the analysis of vectors. So, it is difficult to evaluate the covariance matrices in such a high-dimensional vector ...
Vo Dinh Minh Nhat, Sungyoung Lee
ICPR
2000
IEEE
16 years 7 months ago
Growing Gaussian Mixture Models for Pose Invariant Face Recognition
A major challenge for face recognition algorithms lies in the variance faces undergo while changing pose. This problem is typically addressed by building view dependent models bas...
Ralph Gross, Jie Yang, Alex Waibel
AMFG
2007
IEEE
216views Biometrics» more  AMFG 2007»
16 years 21 days ago
Single Image Subspace for Face Recognition
Small sample size and severe facial variation are two challenging problems for face recognition. In this paper, we propose the SIS (Single Image Subspace) approach to address these...
Jun Liu, Songcan Chen, Zhi-Hua Zhou, Xiaoyang Tan