Probabilistic Modeling of Real-world Scenes in a Virtual Environment

Frank Dittrich, Stephan Irgenfried, Heinz Woern

2015

Abstract

In this paper we present an approach for the automated creation of real-world scenes in an virtual environment. Here we focus on human-robot interaction and collaboration in the industrial domain, with corresponding virtual object classes and inter-class constellations. As the basis for the sample generation process, we probabilistically model essential discrete and continuous object parameters, by adapting a generic mixed joint density function to distinct scene classes, in order to capture the specific inter- and intra-class dependencies. To provide a convenient way to assert these object interactions, we use a Bayesian Network for the representation of the density function, where dependencies can directly be modeled by the network layout. For the conditioned and uncertain descriptions of object translations, we use hierarchical Gaussian Mixture Models as geometrical sampling primitives in the 3D space. In our paper, we show how the combination of a Bayesian Network with these sampling primitives can directly be used for the automated collision avoidance of objects, during the sampling process. For the illustration of the applicability and usefulness of our approach, we instantiate the generic and abstract concept using an example with reduced complexity.

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Paper Citation


in Harvard Style

Dittrich F., Irgenfried S. and Woern H. (2015). Probabilistic Modeling of Real-world Scenes in a Virtual Environment . In Proceedings of the 10th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2015) ISBN 978-989-758-087-1, pages 165-173. DOI: 10.5220/0005313301650173

in Bibtex Style

@conference{grapp15,
author={Frank Dittrich and Stephan Irgenfried and Heinz Woern},
title={Probabilistic Modeling of Real-world Scenes in a Virtual Environment},
booktitle={Proceedings of the 10th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2015)},
year={2015},
pages={165-173},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005313301650173},
isbn={978-989-758-087-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2015)
TI - Probabilistic Modeling of Real-world Scenes in a Virtual Environment
SN - 978-989-758-087-1
AU - Dittrich F.
AU - Irgenfried S.
AU - Woern H.
PY - 2015
SP - 165
EP - 173
DO - 10.5220/0005313301650173