Classifying high-dimensional numerical data is a very challenging problem. In high dimensional feature spaces, the performance of supervised learning methods suffer from the curse...
Methods for expanding the dynamic range of digital photographs by combining images taken at different exposures have recently received a lot of attention. Current techniques assum...
Chris Pal, Richard Szeliski, Matthew Uyttendaele, ...
Active contour models are among the most popular PDE-based tools in computer vision. In this paper we present a new algorithm for the fast evolution of geodesic active contours an...
Reconstructing 3D scenes with independently moving objects from uncalibrated monocular image sequences still poses serious challenges. One important problem is to find the relativ...
Kemal Egemen Ozden, Kurt Cornelis, Luc Van Eycken,...
In this paper, we introduce the notion of a programmable imaging system. Such an imaging system provides a human user or a vision system significant control over the radiometric a...
The problem of deciding whether two pixels in an image have the same real world color is a fundamental problem in computer vision. Many color spaces are used in different applicat...
A unified approach for treating the scale selection problem in the anisotropic scale-space is proposed. The anisotropic scale-space is a generalization of the classical isotropic ...
We examine the stereo correspondence problem in the presence of slanted scene surfaces. In particular, we highlight a previously overlooked geometric fact: a horizontally slanted ...
The problem of estimating an illumination distribution from images is called inverse lighting. For inverse lighting, three approaches have been developed based on specular reflect...
We present a novel structure-enhancing adaptive filter guided by features derived from the Gradient Structure Tensor. We employ this filter to reduce noise in seismic data and to ...