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MEYER, F. KROPFREITER, T. WILLIAMS, J. L. LAU, R. A. HLAWATSCH, F. BRACA, P. WIN, M. Z.
Original Title
Message Passing Algorithms for Scalable Multitarget Tracking
Type
journal article in Web of Science
Language
English
Original Abstract
Situation-aware technologies enabled by multitarget tracking will lead to new services and applications in fields such as autonomous driving, indoor localization, robotic networks, and crowd counting. In this tutorial paper, we advocate a recently proposed paradigm for scalable multitarget tracking that is based on message passing or, more concretely, the loopy sum-product algorithm. This approach has advantages regarding estimation accuracy, computational complexity, and implementation flexibility. Most importantly, it provides a highly effective, efficient, and scalable solution to the probabilistic data association problem, a major challenge in multitarget tracking. This fact makes it attractive for emerging applications requiring real-time operation on resource-limited devices. In addition, the message passing approach is intuitively appealing and suited to nonlinear and non-Gaussian models.
Keywords
Data association; data fusion; factor graph; message passing; multitarget tracking; sum-product algorithm
Authors
MEYER, F.; KROPFREITER, T.; WILLIAMS, J. L.; LAU, R. A.; HLAWATSCH, F.; BRACA, P.; WIN, M. Z.
Released
8. 2. 2018
ISBN
0018-9219
Periodical
PROCEEDINGS OF THE IEEE
Year of study
106
Number
2
State
United States of America
Pages from
221
Pages to
259
Pages count
39
BibTex
@article{BUT153414, author="Florian {Meyer} and Thomas {Kropfreiter} and Jason {Williams} and Roslyn {Lau} and Franz {Hlawatsch} and Paolo {Braca} and Moe {Win}", title="Message Passing Algorithms for Scalable Multitarget Tracking", journal="PROCEEDINGS OF THE IEEE", year="2018", volume="106", number="2", pages="221--259", doi="10.1109/JPROC.2018.2789427", issn="0018-9219" }