Abstract. We propose a method of unsupervised learning from stationary, vector-valued processes. A low-dimensional subspace is selected on the basis of a criterion which rewards da...
The aim of this paper is to propose tools for statistical analysis of shape families using morphological operators. Given a series of shape families (or shape categories), the appr...
Finding point correspondences which are consistent with a geometric constraint is one of the cornerstones of many computer vision problems. This is a difficult task because of sp...
We present a spatially variant framework for correcting uneven illumination and color cast, problems commonly associated with digitized books. The core of our method is a color im...
We describe a method to segment rectangular objects that lie on a slightly textured background of an a-priori unknown colour. Our contribution consists of a fast and accurate back...