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...
The variations of pose lead to significant performance
decline in face recognition systems, which is a bottleneck
in face recognition. A key problem is how to measure the
simila...
Annan Li (Chinese Academy of Sciences), Shiguang S...
—We address the problem of face recognition by matching image sets. Each set of face images is represented by a subspace (or linear manifold) and recognition is carried out by su...
A new local feature based image representation method is proposed. It is derived from the local Gabor phase difference pattern (LGPDP). This method represents images by exploiting ...
Yimo Guo, Guoying Zhao, Jie Chen, Matti Pietik&aum...
This paper proposes a novel nonlinear discriminant analysis method named by Kernerlized Maximum Average Margin Criterion (KMAMC), which has combined the idea of Support Vector Mac...