Image variability due to changes in pose and illumination can seriously impair object
recognition. This paper presents appearance-based methods which, unlike previous …

Due to illumination variability, the same object can appear dramatically different even when
viewed in fixed pose. To handle this variability, an object recognition system must employ a …

Sensitivity to variations in pose is a challenging problem in face recognition using
appearance-based methods. More specifically, the appearance of a face changes …

We present a generative appearance-based method for recognizing human faces under
variation in lighting and viewpoint. Our method exploits the fact that the set of images of an …

When recognizing a fixed object from a fixed viewpoint, the dominant source of variation in
image intensity is lighting changes. We propose a low-dimensional model for human faces …

Most contemporary face recognition algorithms work well under laboratory conditions but
degrade when tested in less-controlled environments. This is mostly due to the difficulty of …

Unconstrained illumination and pose variation lead to significant variation in the
photographs of faces and constitute a major hurdle preventing the widespread use of face …

We consider the problem of determining functions of an image of an object that are
insensitive to illumination changes. We first show that for an object with Lambertian …

Face images are difficult to interpret because they are highly variable. Sources of variability
include individual appearance, 3D pose, facial expression and lighting. We describe a …

We present a unified framework for modeling intrinsic properties of face images for
recognition. It is based on the quotient image (QI) concept, in particular on the existing works …