We present a novel boosting algorithm, called SoftBoost, designed for sets of binary labeled examples that are not necessarily separable by convex combinations of base hypotheses....
Manfred K. Warmuth, Karen A. Glocer, Gunnar Rä...
Confidence measures for the generalization error are crucial when small training samples are used to construct classifiers. A common approach is to estimate the generalization err...
Deformable model fitting has been actively pursued in the computer vision community for over a decade. As a result, numerous approaches have been proposed with varying degrees of ...
We address the problem of regional color transfer between two natural images by probabilistic segmentation. We use a new Expectation-Maximization (EM) scheme to impose both spatia...
Many algorithms for shape analysis and shape processing rely on accurate estimates of differential information such as normals and curvature. In most settings, however, care must...