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» Separable PCA for image classification
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ICPR
2010
IEEE
15 years 4 months ago
On the Dimensionality Reduction for Sparse Representation Based Face Recognition
Face recognition (FR) is an active yet challenging topic in computer vision applications. As a powerful tool to represent high dimensional data, recently sparse representation bas...
Lei Zhang, Meng Yang, Zhizhao Feng, David Zhang
ICPR
2006
IEEE
15 years 5 months ago
Unsupervised Discriminant Projection Analysis for Feature Extraction
This paper develops an unsupervised discriminant projection (UDP) technique for feature extraction. UDP takes the local and non-local information into account, seeking to find a p...
Jian Yang, David Zhang, Zhong Jin, Jing-Yu Yang
IMAGING
2003
15 years 1 months ago
Group Theoretical Invariants in Color Image Processing
Many image formation processes are complex interactions of several sub-processes and the analysis of the resulting images requires often to separate the influence of these sub-pr...
Reiner Lenz, Linh Viet Tran, Thanh Hai Bui
AUSAI
2005
Springer
15 years 5 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
ICIP
2007
IEEE
15 years 6 months ago
Classification by Cheeger Constant Regularization
This paper develops a classification algorithm in the framework of spectral graph theory where the underlying manifold of a high dimensional data set is described by a graph. The...
Hsun-Hsien Chang, José M. F. Moura