Lyudmila Mihaylova
Overview of Bayesian sequential Monte Carlo methods for group and extended object tracking
Mihaylova, Lyudmila; Carmi, Avishy Y.; Septier, François; Gning, Amadou; Pang, Sze Kim; Godsill, Simon
Authors
Avishy Y. Carmi
François Septier
Amadou Gning
Sze Kim Pang
Simon Godsill
Abstract
This work presents the current state-of-the-art in techniques for tracking a number of objects moving in a coordinated and interacting fashion. Groups are structured objects characterized with particular motion patterns. The group can be comprised of a small number of interacting objects (e.g. pedestrians, sport players, convoy of cars) or of hundreds or thousands of components such as crowds of people. The group object tracking is closely linked with extended object tracking but at the same time has particular features which differentiate it from extended objects. Extended objects, such as in maritime surveillance, are characterized by their kinematic states and their size or volume. Both group and extended objects give rise to a varying number of measurements and require trajectory maintenance. An emphasis is given here to sequential Monte Carlo (SMC) methods and their variants. Methods for small groups and for large groups are presented, including Markov Chain Monte Carlo (MCMC) methods, the random matrices approach and Random Finite Set Statistics methods. Efficient real-time implementations are discussed which are able to deal with the high dimensionality and provide high accuracy. Future trends and avenues are traced.
Citation
Mihaylova, L., Carmi, A. Y., Septier, F., Gning, A., Pang, S. K., & Godsill, S. (2014). Overview of Bayesian sequential Monte Carlo methods for group and extended object tracking. Digital Signal Processing, 25, 1-16. https://doi.org/10.1016/j.dsp.2013.11.006
Journal Article Type | Article |
---|---|
Online Publication Date | Dec 4, 2013 |
Publication Date | 2014-02 |
Deposit Date | Jan 2, 2019 |
Publicly Available Date | Jan 3, 2019 |
Journal | Digital Signal Processing |
Print ISSN | 1051-2004 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 25 |
Pages | 1-16 |
DOI | https://doi.org/10.1016/j.dsp.2013.11.006 |
Keywords | Signal Processing; Electrical and Electronic Engineering |
Public URL | https://hull-repository.worktribe.com/output/1199829 |
Publisher URL | https://www.sciencedirect.com/science/article/pii/S1051200413002716 |
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http://creativecommons.org/licenses/by-nc-nd/3.0/
Copyright Statement
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.
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