CUED Publications database

Calibrating the Gaussian multi-target tracking model

Yildirim, S and Jiang, L and Singh, SS and Dean, TA (2014) Calibrating the Gaussian multi-target tracking model. Statistics and Computing. pp. 1-14. ISSN 0960-3174

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Abstract

We present novel batch and online (sequential) versions of the expectation-maximisation (EM) algorithm for inferring the static parameters of a multiple target tracking (MTT) model. Online EM is of particular interest as it is a more practical method for long data sets since in batch EM, or a full Bayesian approach, a complete browse of the data is required between successive parameter updates. Online EM is also suited to MTT applications that demand real-time processing of the data. Performance is assessed in numerical examples using simulated data for various scenarios. For batch estimation our method significantly outperforms an existing gradient based maximum likelihood technique, which we show to be significantly biased. © 2014 Springer Science+Business Media New York.

Item Type: Article
Uncontrolled Keywords: Expectation-maximization Multiple target tracking Online Parameter estimation Particle filters
Subjects: UNSPECIFIED
Divisions: Div F > Signal Processing and Communications
Depositing User: Cron Job
Date Deposited: 07 Mar 2014 11:21
Last Modified: 08 Dec 2014 02:20
DOI: 10.1007/s11222-014-9456-2