The supervised learning paradigm assumes in general that both training and test data are sampled from the same distribution. When this assumption is violated, we are in the setting...
Progressive addition lenses are a relatively new approach to compensate for defects of the human visual system. While traditional spectacles use rotationally symmetric lenses, pro...
Joachim Loos, Philipp Slusallek, Hans-Peter Seidel
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 ...
Many sources of information relevant to computer vision and machine learning tasks are often underused. One example is the similarity between the elements from a novel source, suc...
Illumination inconsistencies cause serious problems for classical computer vision applications such as tracking and stereo matching. We present a new approach to model illuminatio...