Sensor control for multi-target tracking using Cauchy-Schwarz divergence

Abstract

In this paper, we propose a method for optimal stochastic sensor control, where the goal is to minimise the estimation error in multi-object tracking scenarios. Our approach is based on an information theoretic divergence measure between labelled random finite set densities. The multi-target posteriors are generalised labelled multi-Bernoulli (GLMB… (More)

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Cite this paper

@article{Beard2015SensorCF, title={Sensor control for multi-target tracking using Cauchy-Schwarz divergence}, author={Michael Beard and Ba-Tuong Vo and Ba-Ngu Vo and Sanjeev Arulampalam}, journal={2015 18th International Conference on Information Fusion (Fusion)}, year={2015}, pages={937-944} }