Many linear discriminant analysis (LDA) and kernel Fisher discriminant analysis (KFD) methods are based on the restrictive assumption that the data are homoscedastic. In this paper...
Locally Linear Embedding (LLE) has recently been proposed as a method for dimensional reduction of high-dimensional nonlinear data sets. In LLE each data point is reconstructed fro...
Claudio Varini, Andreas Degenhard, Tim W. Nattkemp...
We present a Modular Bilinear Disciminant Analysis (MBDA) approach for face recognition. A set of classifiers are trained independently on specific face regions, and different c...
In this paper we propose a novel data hiding procedure called Quantized Projection (QP), that combines elements from quantization (i.e. Quantization Index Modulation, QIM) and spr...
Face recognition is one of the most challenging biometric modalities for personal identification. This is due to a number of factors, including the complexity and variability of th...