Paper: Scalable Detection and Tracking of Extended Objects
This paper presents a factor graph formulation and sum-product algorithm (SPA) for scalable detection and tracking of extended objects that generate multiple measurements.
The proposed method dynamically introduces newly detected objects into the state space and efficiently performs probabilistic multiple-measurement to object associations.
We demonstrate performance advantages of our method numerically in a challenging tracking scenario with multiple closely-spaced extended objects.
Fig. 2. MOSPA versus time for different tracking algorithms.
F. Meyer and J. L. Williams, “Scalable Detection and Tracking of Extended Objects,” ICASSP 2020 – 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, 2020, pp. 8916-8920, doi: 10.1109/ICASSP40776.2020.9054277.
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