11 papers
Recursive Entropic Variational Inference for Nonlinear State-Space Models
Hany Abdulsamad, Ãngel F. GarcÃa-Fernández, Simo Särkkä
We present a class of algorithms for state estimation in nonlinear, non-Gaussian state-space models. Our approach is based on a variational Lagrangian formulation that casts Bayesi…
Variational PMB filter via coordinate descent Kullback-Leibler divergence minimisation
Ãngel F. GarcÃa-Fernández, Yuxuan Xia
This paper presents a new derivation of the variational Poisson multi-Bernoulli (V-PMB) filter for multi-target estimation proposed in [#Williams15]. The proposed derivation is bas…
Efficient Implementations of Extended Object PMBM Filters with Blocked Gibbs Sampling
Yuxuan Xia, Ãngel F. GarcÃa-Fernández, Lennart Svensson
This paper considers multiple extended object tracking based on Poisson multi-Bernoulli mixture (PMBM) filtering, which gives the closed-form Bayesian solution for standard multipl…
GOSPA and T-GOSPA quasi-metrics for evaluation of multi-object tracking algorithms
Ãngel F. GarcÃa-Fernández, Jinhao Gu, Lennart Svensson +4
This paper introduces two quasi-metrics for performance assessment of multi-object tracking (MOT) algorithms. One quasi-metric is an extension of the generalised optimal subpattern…
A Track-Before-Detect Trajectory Multi-Bernoulli Filter for Generalised Superpositional Measurements
Sion Lynch, Ãngel F. GarcÃa-Fernández, Lee Devlin
This paper proposes the Trajectory-Information Exchange Multi-Bernoulli (T-IEMB) filter to estimate sets of alive and all trajectories in track-before-detect applications with gene…
TGOSPA Metric Parameters Selection and Evaluation for Visual Multi-object Tracking
Jan KrejÄÃ, Oliver Kost, OndÅej Straka +3
Multi-object tracking algorithms are deployed in various applications, each with different performance requirements. For example, track switches pose significant challenges for off…