Seamless exchange of models among different modeling tools increasingly becomes a crucial prerequisite for the success of modeldriven engineering. Current best practices use model ...
Gerti Kappel, Horst Kargl, Thomas Reiter, Werner R...
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
Fitting data by a bounded complexity linear model is equivalent to low-rank approximation of a matrix constructed from the data. The data matrix being Hankel structured is equival...
Nearly every structured prediction problem in computer vision requires approximate inference due to large and complex dependencies among output labels. While graphical models prov...
Abstract. Accurate registration of cortical structures plays a fundamental role in statistical analysis of brain images across population. This paper presents a novel framework for...