Upper Bound Tracker: A Multi-Animal Tracking Solution for Closed Laboratory Settings

Alexander Dolokov, Niek Andresen, Niek Andresen, Katharina Hohlbaum, Christa Thöne-Reineke, Christa Thöne-Reineke, Lars Lewejohann, Lars Lewejohann, Lars Lewejohann, Olaf Hellwich, Olaf Hellwich

2023

Abstract

When tracking multiple identical objects or animals in video, many erroneous results are implausible right away, because they ignore a fundamental truth about the scene. Often the number of visible targets is bounded. This work introduces a multiple object pose estimation solution for the case that this upper bound is known. It dismisses all detections that would exceed the maximally permitted number and is able to re-identify an individual after an extended period of occlusion including the re-appearance in a different place. An example dataset with four freely interacting laboratory mice is additionally introduced and the tracker’s performance demonstrated on it. The dataset contains various conditions ranging from almost no opportunity to hide for the mice to a fairly cluttered environment. The approach is able to significantly reduce the occurrences of identity switches - the error when a known individual is suddenly identified as a different one - compared to other current solutions.

Download


Paper Citation


in Harvard Style

Dolokov A., Andresen N., Hohlbaum K., Thöne-Reineke C., Lewejohann L. and Hellwich O. (2023). Upper Bound Tracker: A Multi-Animal Tracking Solution for Closed Laboratory Settings. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP; ISBN 978-989-758-634-7, SciTePress, pages 945-952. DOI: 10.5220/0011609500003417


in Bibtex Style

@conference{visapp23,
author={Alexander Dolokov and Niek Andresen and Katharina Hohlbaum and Christa Thöne-Reineke and Lars Lewejohann and Olaf Hellwich},
title={Upper Bound Tracker: A Multi-Animal Tracking Solution for Closed Laboratory Settings},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP},
year={2023},
pages={945-952},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011609500003417},
isbn={978-989-758-634-7},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP
TI - Upper Bound Tracker: A Multi-Animal Tracking Solution for Closed Laboratory Settings
SN - 978-989-758-634-7
AU - Dolokov A.
AU - Andresen N.
AU - Hohlbaum K.
AU - Thöne-Reineke C.
AU - Lewejohann L.
AU - Hellwich O.
PY - 2023
SP - 945
EP - 952
DO - 10.5220/0011609500003417
PB - SciTePress