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Author: Nathanael L. Baisa

Affiliation: University of Lincoln, United Kingdom

Keyword(s): Visual Tracking, Multiple Target Filtering, MHT, PHD Filter, HISP Filter, MOT Challenge.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Motion, Tracking and Stereo Vision ; Tracking and Visual Navigation ; Video Surveillance and Event Detection

Abstract: We propose a new multi-target visual tracker based on the recently developed Hypothesized and Independent Stochastic Population (HISP) filter. The HISP filter combines advantages of traditional tracking approaches like multiple hypothesis tracking (MHT) and point-process-based approaches like probability hypothesis density (PHD) filter, and has a linear complexity while maintaining track identities. We apply this filter for tracking multiple targets in video sequences acquired under varying environmental conditions and targets density using a tracking-by-detection approach. In addition, we alleviate the problem of two or more targets having identical label taking into account the weight propagated with each confirmed hypothesis. Finally, we carry out extensive experiments on Multiple Object Tracking 2016 (MOT16) benchmark dataset and find out that our tracker significantly outperforms several state-of-the-art trackers in terms of tracking accuracy.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Baisa, N. (2018). Online Multi-target Visual Tracking using a HISP Filter. In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 5: VISAPP; ISBN 978-989-758-290-5; ISSN 2184-4321, SciTePress, pages 429-438. DOI: 10.5220/0006564504290438

@conference{visapp18,
author={Nathanael L. Baisa.},
title={Online Multi-target Visual Tracking using a HISP Filter},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 5: VISAPP},
year={2018},
pages={429-438},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006564504290438},
isbn={978-989-758-290-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 5: VISAPP
TI - Online Multi-target Visual Tracking using a HISP Filter
SN - 978-989-758-290-5
IS - 2184-4321
AU - Baisa, N.
PY - 2018
SP - 429
EP - 438
DO - 10.5220/0006564504290438
PB - SciTePress