In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...
Extending a differential total least squares method for range flow estimation we present an iterative regularisation approach to compute dense range flow fields. We demonstrate how...
The method of Moving Least Squares (MLS) is a popular framework for reconstructing continuous functions from scattered data due to its rich mathematical properties and well-underst...
Christian Ledergerber, Gaël Guennebaud, Miriah ...
Defining sharp features in a given 3D model facilitates a better understanding of the surface and aids visualizations, reverse engineering, filtering, simplification, non-photo...
Joel Daniels II, Linh K. Ha, Tilo Ochotta, Cl&aacu...
Many of the computer vision algorithms have been posed in various forms of differential equations, derived from minimization of specific energy functionals, and the finite eleme...