In this research we address the problem of classification and labeling of regions given a single static natural image. Natural images exhibit strong spatial dependencies, and mode...
A direct algorithm to estimate continuous-time ARMA (CARMA) models is proposed in this paper. In this approach, we first pass the observed data through an input-to-state filter an...
In this paper we present Discriminative Random Fields (DRF), a discriminative framework for the classification of natural image regions by incorporating neighborhood spatial depe...
: We are presenting a tool for collecting and analysing computer usage data. The observed data are locally used by the user to self-monitor and self-reflect her behaviour, decontro...
Maren Scheffel, Martin Friedrich, Marco Jahn, Uwe ...
Abstract. In Minimum Message Length (MML) clustering (unsupervised classification, mixture modelling) the aim is to infer a set of classes that best explains the observed data ite...
Abstract— In this paper, we propose a deformable-modeldriven method to recognize the state of hanging clothes using three-dimensional (3D) observed data. For the task to pick up ...
Yasuyo Kita, Toshio Ueshiba, Ee Sian Neo, Nobuyuki...
We address the problem of detecting irregularities in visual data, e.g., detecting suspicious behaviors in video sequences, or identifying salient patterns in images. The term &qu...