Calibrating the Gaussian multi-target tracking model
Calibrating the Gaussian multi-target tracking model
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DOI：
10.1007/s11222-014-9456-2
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发表时间：
2014-02
影响因子：
2.2
通讯作者：
S. Yıldırım;Lan Jiang;Sumeetpal S. Singh;Thomas Dean
中科院分区：
文献类型：
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作者：
S. Yıldırım;Lan Jiang;Sumeetpal S. Singh;Thomas Dean
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.
