93 citations · 247 across the 22 of their papers we have counts for
22 papers
Variational PMB filter via coordinate descent Kullback-Leibler divergence minimisation
Ángel F. García-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, Ángel F. García-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…
Recursive Entropic Variational Inference for Nonlinear State-Space Models
Hany Abdulsamad, Ángel F. García-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…
A Scalable Hybrid Track-Before-Detect Tracking System: Application to Coastal Maritime Radar Surveillance
Lukas Herrmann, Ángel F. García-Fernández, Edmund F. Brekke +1
Despite their theoretical advantages, track-before-detect (TBD) methods remain largely absent from real-world multi-target tracking applications due to their computational complexi…
GOSPA and T-GOSPA quasi-metrics for evaluation of multi-object tracking algorithms
Ángel F. García-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…
Probabilistic Trajectory GOSPA: A Metric for Uncertainty-Aware Multi-Object Tracking Performance Evaluation
Yuxuan Xia, Ángel F. García-Fernández, Johan Karlsson +3
This paper presents a generalization of the trajectory general optimal sub-pattern assignment (GOSPA) metric for evaluating multi-object tracking algorithms that provide trajectory…
Probabilistic GOSPA: A Metric for Performance Evaluation of Multi-Object Filters with Uncertainties
Yuxuan Xia, Ángel F. García-Fernández, Johan Karlsson +3
This paper presents a probabilistic generalization of the Generalized Optimal Sub-Pattern Assignment (GOSPA) metric, termed P-GOSPA. The GOSPA metric has been widely used to evalua…
TGOSPA Metric Parameters Selection and Evaluation for Visual Multi-object Tracking
Jan Krejčí, Oliver Kost, Ondřej 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…
Hybrid PHD-PMB Trajectory Smoothing Using Backward Simulation
Yuxuan Xia, Ángel F. García-Fernández, Lennart Svensson
The probability hypothesis density (PHD) and Poisson multi-Bernoulli (PMB) filters are two popular set-type multi-object filters. Motivated by the fact that the multi-object filter…
Batch SLAM with PMBM Data Association Sampling and Graph-Based Optimization
Yu Ge, Ossi Kaltiokallio, Yuxuan Xia +6
Simultaneous localization and mapping (SLAM) methods need to both solve the data association (DA) problem and the joint estimation of the sensor trajectory and the map, conditioned…
Markov Chain Monte Carlo Multi-Scan Data Association for Sets of Trajectories
Yuxuan Xia, Ángel F. García-Fernández, Lennart Svensson
This paper considers a batch solution to the multi-object tracking problem based on sets of trajectories. Specifically, we present two offline implementations of the trajectory Poi…
Poisson multi-Bernoulli mixture filter with general target-generated measurements and arbitrary clutter
Ángel F. García-Fernández, Yuxuan Xia, Lennart Svensson
This paper shows that the Poisson multi-Bernoulli mixture (PMBM) density is a multi-target conjugate prior for general target-generated measurement distributions and arbitrary clut…
A comparison between PMBM Bayesian track initiation and labelled RFS adaptive birth
Ángel F. García-Fernández, Yuxuan Xia, Lennart Svensson
This paper provides a comparative analysis between the adaptive birth model used in the labelled random finite set literature and the track initiation in the Poisson multi-Bernoull…
Trajectory PMB Filters for Extended Object Tracking Using Belief Propagation
Yuxuan Xia, Ángel F. García-Fernández, Florian Meyer +3
In this paper, we propose a Poisson multi-Bernoulli (PMB) filter for extended object tracking (EOT), which directly estimates the set of object trajectories, using belief propagati…
Multiple Object Trajectory Estimation Using Backward Simulation
Yuxuan Xia, Lennart Svensson, Ángel F. García-Fernández +3
This paper presents a general solution for computing the multi-object posterior for sets of trajectories from a sequence of multi-object (unlabelled) filtering densities and a mult…
A Poisson multi-Bernoulli mixture filter for coexisting point and extended targets
Ángel F. García-Fernández, Jason L. Williams, Lennart Svensson +1
This paper proposes a Poisson multi-Bernoulli mixture (PMBM) filter for coexisting point and extended targets, i.e., for scenarios where there may be simultaneous point and extende…
Backward Simulation for Sets of Trajectories
Yuxuan Xia, Lennart Svensson, Ángel F. García-Fernández +2
This paper presents a solution for recovering full trajectory information, via the calculation of the posterior of the set of trajectories, from a sequence of multitarget (unlabell…
Trajectory Poisson multi-Bernoulli filters
Ángel F. García-Fernández, Lennart Svensson, Jason L. Williams +2
This paper presents two trajectory Poisson multi-Bernoulli (TPMB) filters for multi-target tracking: one to estimate the set of alive trajectories at each time step and another to…
Poisson Multi-Bernoulli Mixtures for Sets of Trajectories
Karl Granström, Lennart Svensson, Yuxuan Xia +2
The Poisson Multi-Bernoulli Mixture (PMBM) density is a conjugate multi-target density for the standard point target model with Poisson point process birth. This means that both th…
Multi-Scan Implementation of the Trajectory Poisson Multi-Bernoulli Mixture Filter
Yuxuan Xia, Karl Granström, Lennart Svensson +2
The Poisson multi-Bernoulli mixture (PMBM) and the multi-Bernoulli mixture (MBM) are two multi-target distributions for which closed-form filtering recursions exist. The PMBM has a…
Extended target Poisson multi-Bernoulli mixture trackers based on sets of trajectories
Yuxuan Xia, Karl Granström, Lennart Svensson +2
The Poisson multi-Bernoulli mixture (PMBM) is a multi-target distribution for which the prediction and update are closed. By applying the random finite set (RFS) framework to multi…
Poisson Multi-Bernoulli Approximations for Multiple Extended Object Filtering
Yuxuan Xia, Karl Granström, Lennart Svensson +3
The Poisson multi-Bernoulli mixture (PMBM) is a multi-object conjugate prior for the closed-form Bayes random finite sets filter. The extended object PMBM filter provides a closed-…