Linear Complexity Gibbs Sampling for Generalized Labeled Multi-Bernoulli Filtering
Published in IEEE Transactions on Signal Processing, 2023
This paper presents a linear complexity Gibbs sampling approach for Generalized Labeled Multi-Bernoulli (GLMB) filtering, significantly reducing the computational burden of multi-object state estimation.
Recommended citation: C. Shim, B.T. Vo, B.N. Vo, J. Ong, and D. Moratuwage (2023). "Linear Complexity Gibbs Sampling for Generalized Labeled Multi-Bernoulli Filtering." IEEE Transactions on Signal Processing, 71, 1981-1994.
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