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Deterministic Multi-sensor Measurement-adaptive Birth using Labeled Random Finite Sets
A truncation procedure has also been provided that leverages a stochastic Gibbs sampler to truncate the birth density for scalability.
On Gibbs Sampling Architecture for Labeled Random Finite Sets Multi-Object Tracking
However, only a limited discussion has been provided regarding key Gibbs sampler architecture details including the Markov chain Monte Carlo sample generation technique and early termination criteria.
Multi-sensor Joint Adaptive Birth Sampler for Labeled Random Finite Set Tracking
A naive construction of the multi-sensor measurement adaptive birth set distribution leads to an exponential number of newborn components in the number of sensors.
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