Linear Discriminant Analysis (LDA) is a well-known scheme for feature extraction and dimension reduction. It has been used widely in many applications involving high-dimensional d...
This paper is about a curious phenomenon. Suppose we have a data matrix, which is the superposition of a low-rank component and a sparse component. Can we recover each component i...
: As an extension to 2DPCA, Generalized Low Rank Approximation of Matrices (GLRAM) applies two-sided (i.e., the left and right) rather than single-sided (i.e., the left or the righ...
Independent Components Analysis (ICA) maximizes the statistical independence of the representational components of a training image ensemble, but it cannot distinguish between the...
In this paper we present an environment for the tracking of a human face obtained from a real video sequence. We will describe the system and discuss the advantages and disadvanta...