One approach to pattern classification is to match a structural description of a pattern to
models which describe the structural properties of pattern classes. The central problem in …

Large calibrated datasets of'random'natural images have recently become available. These
make possible precise and intensive statistical studies of the local nature of images. We …

Automatic classification is one of the basic tasks required in any pattern recognition and
human computer interaction application. In this paper, we discuss training probabilistic …

Vision has to deal with uncertainty. The sensors are noisy, the prior knowledge is uncertain
or inaccurate, and the problems of recovering scene information from images are often ill …

We define a probability distribution over equivalence classes of binary matrices with a finite
number of rows and an unbounded number of columns. This distribution is suitable for use …

The Riemannian geometry of covariance matrices has been essential to several successful
applications, in computer vision, biomedical signal and image processing, and radar data …

In various application domains, including image recognition, it is natural to represent each
example as a set of vectors. With a base kernel we can implicitly map these vectors to a …

Computer vision researchers are developing new approaches to object recognition and
detection that are based almost directly on images and avoid the use of intermediate three …