We present a new method that we call Generalized Discriminant Analysis (GDA) to deal with nonlinear discriminant analysis using kernel function operator. The underlying theory is ...
— Kernel mapping is one of the most used approaches to intrinsically derive nonlinear classifiers. The idea is to use a kernel function which maps the original nonlinearly separ...
We present a comprehensive approach to address three challenging problems in face recognition: modelling faces across multi-views, extracting the non-linear discriminating feature...
It is known that no single descriptor is powerful enough to encompass all aspects of image content, i.e. each feature extraction method has its own view of the image content. A pos...
Lin Mei, Gerd Brunner, Lokesh Setia, Hans Burkhard...