Random subspaces are a popular ensemble construction technique that improves the accuracy of weak classifiers. It has been shown, in different domains, that random subspaces combi...
Traditional face superresolution methods treat face images as 1D vectors and apply PCA on the set of these 1D vectors to learn the face subspace. Zhang et al [7] proposed Two-dire...
In [1], three popular subspace face recognition methods, PCA, Bayes, and LDA were analyzed under the same framework and an unified subspace analysis was proposed. However, since t...
LDA is a popular subspace based face recognition approach. However, it often suffers from the small sample size problem. When dealing with the high dimensional face data, the LDA ...
We consider the problem of recognizing 3-D objects from 2-D images using geometric models and assuming different viewing angles and positions. Our goal is to recognize and localize...