We prove that the set of all Lambertian reflectance functions (the mapping from surface
normals to intensities) obtained with arbitrary distant light sources lies close to a 9D linear …

We introduce two appearance-based methods for clustering a set of images of 3D (three-
dimensional) objects, acquired under varying illumination conditions, into disjoint subsets …

Face images that are captured by surveillance cameras usually have a very low resolution,
which significantly limits the performance of face recognition systems. In the past, super …

Face recognition algorithms have to deal with significant amounts of illumination variations
between gallery and probe images. State-of-the-art commercial face recognition algorithms …

Abstract Density estimation with Gaussian Mixture Models is a popular generative technique
used also for clustering. We develop a framework to incorporate side information in the form …

Recognition systems have generally treated specular highlights as noise. We show how to
use these highlights as a positive source of information that improves recognition of shiny …

We present a general framework for face modeling under varying lighting conditions. First,
we show that a face lighting subspace can be constructed based on three or more training …

In this paper, a face recognition algorithm using multi feature and Radial basis Function
Network (RBFN) is proposed. The algorithm consists of three steps. In the first step, a coarse …

The paper is about learning using partial information in the form of equivalence constraints.
Equivalence constraints provide relational information about the labels of data points, rather …

Illumination ratio images are presented in the paper to illuminate the faces. Our rendering
method can simulate the distribution of the images with varying illuminations and generate …