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Overview of Bayesian sequential Monte Carlo methods for group and extended object tracking (2013)
Journal Article
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

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... Read More about Overview of Bayesian sequential Monte Carlo methods for group and extended object tracking.

Box-particle probability hypothesis density filtering (2013)
Journal Article
Schikora, M., Gning, A., Mihaylova, L., Cremers, D., & Koch, W. (2014). Box-particle probability hypothesis density filtering. IEEE Transactions on Aerospace and Electronic Systems, 50(3), 1660-1672. https://doi.org/10.1109/taes.2014.120238

This paper develops a novel approach for multitarget tracking, called box-particle probability hypothesis density filter (box-PHD filter). The approach is able to track multiple targets and estimates the unknown number of targets. Furthermore, it is... Read More about Box-particle probability hypothesis density filtering.


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