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Authors: Nathanael L. Baisa and Andrew Wallace

Affiliation: Heriot Watt University, United Kingdom

Keyword(s): Visual Tracking, Random Finite Set, Multiple Target Filtering, Gaussian Mixture, Tri-GM-PHD Filter, OSPA Metric.

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 framework that extends the standard Probability Hypothesis Density (PHD) filter for multiple targets having three different types, taking into account not only background false positives (clutter), but also confusion between detections of different target types, which are in general different in character from background clutter. Our framework extends the existing Gaussian Mixture (GM) implementation of the PHD filter to create a tri-GM-PHD filter based on Random Finite Set (RFS) theory. The methodology is applied to real video sequences containing three types of multiple targets in the same scene, two football teams and a referee, using separate detections. Subsequently, Munkres’s variant of the Hungarian assignment algorithm is used to associate tracked target identities between frames. This approach is evaluated and compared to both raw detections and independent GM-PHD filters using the Optimal Sub-pattern Assignment (OSPA) metric and discrimination rate. This sh ows the improved performance of our strategy on real video sequences. (More)

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Paper citation in several formats:
L. Baisa, N. and Wallace, A. (2017). Multiple Target, Multiple Type Visual Tracking using a Tri-GM-PHD Filter. In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 6: VISAPP; ISBN 978-989-758-227-1; ISSN 2184-4321, SciTePress, pages 467-477. DOI: 10.5220/0006145704670477

@conference{visapp17,
author={Nathanael {L. Baisa}. and Andrew Wallace.},
title={Multiple Target, Multiple Type Visual Tracking using a Tri-GM-PHD Filter},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 6: VISAPP},
year={2017},
pages={467-477},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006145704670477},
isbn={978-989-758-227-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 6: VISAPP
TI - Multiple Target, Multiple Type Visual Tracking using a Tri-GM-PHD Filter
SN - 978-989-758-227-1
IS - 2184-4321
AU - L. Baisa, N.
AU - Wallace, A.
PY - 2017
SP - 467
EP - 477
DO - 10.5220/0006145704670477
PB - SciTePress