We propose a framework for 3D geometry processing that provides direct access to surface curvature to facilitate advanced shape editing, filtering, and synthesis algorithms. The c...
This paper addresses the problem of estimating the 3D rigid pose of an object from its digitized X-ray projection. We considered the cases of homogeneous (CAD models) and inhomoge...
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
We derive categories directly from robot sensor data to address the symbol grounding problem. Unlike model-based approaches where human intuitive correspondences are sought betwee...
Daniel H. Grollman, Odest Chadwicke Jenkins, Frank...
Kernels are two-placed functions that can be interpreted as inner products in some Hilbert space. It is this property which makes kernels predestinated to carry linear models of l...