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...
We present a fast and robust system for estimating structure
and motion using a stereo pair, with straight lines as
features. Our first set of contributions are efficient algorit...
Background subtraction algorithms define the background
as parts of a scene that are at rest. Traditionally,
these algorithms assume a stationary camera, and identify
moving obj...
We present a new variational level-set-based segmentation
formulation that uses both shape and intensity prior information
learned from a training set. By applying Bayes’
rule...
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...