no code implementations • 23 Apr 2020 • Jonas Geiping, Fjedor Gaede, Hartmut Bauermeister, Michael Moeller
We discuss this methodology in detail and show examples in multi-label segmentation by minimal partitions and stereo estimation, where we demonstrate that the proposed graph discretization can reduce runtime as well as memory consumption of convex relaxations of matching problems by up to a factor of 10.
no code implementations • 7 Mar 2019 • Daniel Tenbrinck, Fjedor Gaede, Martin Burger
In this paper we propose a variational method defined on finite weighted graphs, which allows to sparsify a given 3D point cloud while giving the flexibility to control the appearance of the resulting approximation based on the chosen regularization functional.
Numerical Analysis Discrete Mathematics Data Structures and Algorithms Optimization and Control