Multi-view Real-time 3D Occupancy Map for Machine-patient Collision Avoidance

Timothy Callemein, Kristof Van Beeck, Toon Goedemé

2021

Abstract

Nowadays - due to advancements in technology - cooperative robots (or cobots) find their way outside the more traditional industrial context. They are used for example in medical scenarios during operations or scanning of patients. Evidently, these scenarios require sufficient safety measures. In this work, we focus on the scenario of an X-ray scanner room, equipped with several cobots (mobile scanner, adjustable tabletop and wall stand) where both patients and medical staff members can walk around freely. We propose an approach to calculate a 3D safeguard zone around people that can be used to restrict the movement of the cobots to prevent collisions. For this, we rely on four ceiling-mounted cameras. The goal of this work is to develop an accurate system with minimal latency at limited hardware costs. To calculate the 3D safeguard zone we propose to use CNN people detection or segmentation techniques to provide the silhouette input needed to calculate a 3D visual hull. We evaluate several state-of-the-art techniques in the search of the optimal trade-off between speed and accuracy. Our research shows that it is possible to achieve acceptable performance processing four cameras with a latency of 125ms with a precision of 54% at a recall of 75%, using the YOLACT++ model.

Paper Citation

in Harvard Style

Callemein T., Van Beeck K. and Goedemé T. (2021). Multi-view Real-time 3D Occupancy Map for Machine-patient Collision Avoidance. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP; ISBN 978-989-758-488-6, SciTePress, pages 627-636. DOI: 10.5220/0010151906270636

in Bibtex Style

@conference{visapp21,
author={Timothy Callemein and Kristof Van Beeck and Toon Goedemé},
title={Multi-view Real-time 3D Occupancy Map for Machine-patient Collision Avoidance},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP},
year={2021},
pages={627-636},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010151906270636},
isbn={978-989-758-488-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP
TI - Multi-view Real-time 3D Occupancy Map for Machine-patient Collision Avoidance
SN - 978-989-758-488-6
AU - Callemein T.
AU - Van Beeck K.
AU - Goedemé T.
PY - 2021
SP - 627
EP - 636
DO - 10.5220/0010151906270636
PB - SciTePress