Pedestrian Tracking using a Generalized Potential Field Approach

Florian Particke, Lucila Patiño-Studencki, Jörn Thielecke, Christian Feist

2017

Abstract

Mobile robots and autonomous driving cars operate in a shared environment with pedestrians. In order to avoid accidents, it is important to track and predict human trajectories in an optimal way. In this paper, a generalized potential field approach for characterizing pedestrian movements is proposed which goes beyond the well-known social force model. Its goal is to give a generalized architecture for improving the tracking accuracy of pedestrians in surveillance situations. In comparison to other fusion approaches, the number of proposed parameters is reduced and the parameters can be intuitively understood. For a simple scenario, in a forum the trajectories of pedestrians are predicted for a configured parameter set. For this purpose, the proposed model is used. The predicted trajectories are compared to the real trajectories of the pedestrians. First results regarding the accuracy of the approach are presented.

Paper Citation

in Harvard Style

Particke F., Patiño-Studencki L., Thielecke J. and Feist C. (2017). Pedestrian Tracking using a Generalized Potential Field Approach . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-227-1, pages 509-514. DOI: 10.5220/0006215705090514

in Bibtex Style

@conference{visapp17,
author={Florian Particke and Lucila Patiño-Studencki and Jörn Thielecke and Christian Feist},
title={Pedestrian Tracking using a Generalized Potential Field Approach},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={509-514},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006215705090514},
isbn={978-989-758-227-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017)
TI - Pedestrian Tracking using a Generalized Potential Field Approach
SN - 978-989-758-227-1
AU - Particke F.
AU - Patiño-Studencki L.
AU - Thielecke J.
AU - Feist C.
PY - 2017
SP - 509
EP - 514
DO - 10.5220/0006215705090514