Multiple Target, Multiple Type Visual Tracking using a Tri-GM-PHD Filter

Nathanael L. Baisa, Andrew Wallace

2017

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 shows the improved performance of our strategy on real video sequences.

Paper Citation

in Harvard Style

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 - Volume 6: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-227-1, pages 467-477. DOI: 10.5220/0006145704670477

in Bibtex Style

@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 - Volume 6: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={467-477},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006145704670477},
isbn={978-989-758-227-1},
}

in EndNote Style

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