Petrov, Nikolay and Mihaylova, Lyudmila and Gning, Amadou and Angelova, Donka (2012) Group Object Tracking with a Sequential Monte Carlo Method Based on a Parameterised Likelihood Function. In: Monte Carlo Methods and Applications. De Gruyter Proceedings in Mathematics . De Gruyter, pp. 171-180. ISBN 9783110293586Full text not available from this repository.
Group objects are characterised with multiple measurements originating from different locations of the targets constituting the group. This paper presents a novel Sequential Monte Carlo approach for tracking groups with a large number of components, applicable to various nonlinear problems. The novelty in this work is in the derivation of the likelihood function for nonlinear measurement functions, with sets of measurements belonging to a bounded spatial region. Simulation results are presented when a group of 50 objects is surrounded by a circular region. Estimation results are given for the group object center and extent.
|Item Type:||Contribution in Book/Report/Proceedings|
|Uncontrolled Keywords:||sequential Monte Carlo methods ; measurement uncertainty ; nonlinear estimation ; group object tracking|
|Departments:||Faculty of Science and Technology > School of Computing & Communications|
|Deposited On:||17 May 2012 16:51|
|Last Modified:||19 Apr 2016 01:05|
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