We show that for every α > 0, there exist n-point metric spaces (X, d) where every “scale” admits a Euclidean embedding with distortion at most α, but the whole space req...
MAP estimation of Gaussian mixtures through maximisation of penalised likelihoods was used to learn models of spatial context. This enabled prior beliefs about the scale, orientat...
A geometric framework for image scale space, enhancement, and segmentation is presented. We consider intensity images as surfaces in the (x I) space. The image is thereby a 2D surf...
Obscure glass is textured glass designed to separate spaces and “obscure” visibility between the spaces. Such glass is used to provide privacy while still allowing light to fl...
Distance-based methods in machine learning and pattern recognition have to rely on a metric distance between points in the input space. Instead of specifying a metric a priori, we...