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Authors: Martin Ahrnbom 1 ; Mikael Nilsson 1 and Håkan Ardö 2

Affiliations: 1 Centre for Mathematical Sciences, Lund University, Lund, Sweden ; 2 Axis Communications AB, Lund, Sweden

Keyword(s): Multi-target Tracking, Segmentation Tracking, Instance Segmentation, Real-time, Online Tracking.

Abstract: The first online segmentation multi-target tracking algorithm with reported real-time speeds is presented. Based on the popular and fast bounding box based tracker SORT, our method called SORTS is able to utilize segmentations for tracking while keeping the real-time speeds. To handle occlusions, which neither SORT nor SORTS do, we also present SORTS+RReID, an optional extension which uses ReID vectors to revive lost tracks from SORTS to handle occlusions. Despite only computing ReID vectors for 6.9% of the detections, ID switches are decreased by 45%. We evaluate on the MOTS dataset and run at 54.5 and 36.4 FPS for SORTS and SORT+RReID respectively, while keeping 78-79% of the sMOTSA of the current state of the art, which runs at 0.3 FPS. Furthermore, we include an experiment using a faster instance segmentation method to explore the feasibility of a complete real-time detection and tracking system. Code is available: https://github.com/ahrnbom/sorts.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Ahrnbom, M.; Nilsson, M. and Ardö, H. (2021). Real-time and Online Segmentation Multi-target Tracking with Track Revival Re-identification. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP; ISBN 978-989-758-488-6; ISSN 2184-4321, SciTePress, pages 777-784. DOI: 10.5220/0010190907770784

@conference{visapp21,
author={Martin Ahrnbom. and Mikael Nilsson. and Håkan Ardö.},
title={Real-time and Online Segmentation Multi-target Tracking with Track Revival Re-identification},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP},
year={2021},
pages={777-784},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010190907770784},
isbn={978-989-758-488-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 5: VISAPP
TI - Real-time and Online Segmentation Multi-target Tracking with Track Revival Re-identification
SN - 978-989-758-488-6
IS - 2184-4321
AU - Ahrnbom, M.
AU - Nilsson, M.
AU - Ardö, H.
PY - 2021
SP - 777
EP - 784
DO - 10.5220/0010190907770784
PB - SciTePress