Many semi-supervised learning algorithms only
deal with binary classification. Their extension to the
multi-class problem is usually obtained by repeatedly
solving a set of bina...
We propose an unconventional but highly effective approach
to robust fitting of multiple structures by using statistical
learning concepts. We design a novel Mercer kernel
for t...
This paper introduces an unsupervised color segmentation
method. The underlying idea is to segment the input
image several times, each time focussing on a different
salient part...
Michael Donoser, Martin Urschler, Martin Hirzer an...
Calibrating a network of cameras with non-overlapping views is an important and challenging problem in computer vision. In this paper, we present a novel technique for camera cali...
Ram Krishan Kumar, Adrian Ilie, Jan-Michael Frahm,...
We propose a spectral partitioning approach for large-scale optimization problems, specifically structure from motion. In structure from motion, partitioning methods reduce the pr...