364 citations · 1.3k across the 18 of their papers we have counts for
20 papers
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 Scalable Track-Before-Detect Method With Poisson/Multi-Bernoulli Model
Thomas Kropfreiter, Jason L. Williams, Florian Meyer
We propose a scalable track-before-detect (TBD) tracking method based on a Poisson/multi-Bernoulli model. To limit computational complexity, we approximate the exact multi-Bernoull…
Scalable Detection and Tracking of Geometric Extended Objects
Florian Meyer, Jason L. Williams
Multiobject tracking provides situational awareness that enables new applications for modern convenience, public safety, and homeland security. This paper presents a factor graph f…
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…
Spatiotemporal Constraints for Sets of Trajectories with Applications to PMBM Densities
Karl Granström, Lennart Svensson, Yuxuan Xia +2
In this paper we introduce spatiotemporal constraints for trajectories, i.e., restrictions that the trajectory must be in some part of the state space (spatial constraint) at some…
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…
Gaussian implementation of the multi-Bernoulli mixture filter
Ángel F. García-Fernández, Yuxuan Xia, Karl Granström +2
This paper presents the Gaussian implementation of the multi-Bernoulli mixture (MBM) filter. The MBM filter provides the filtering (multi-target) density for the standard dynamic a…
Poisson multi-Bernoulli mixture trackers: continuity through random finite sets of trajectories
Karl Granström, Lennart Svensson, Yuxuan Xia +2
The Poisson multi-Bernoulli mixture (PMBM) is an unlabelled multi-target distribution for which the prediction and update are closed. It has a Poisson birth process, and new Bernou…
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-…
Poisson multi-Bernoulli mixture filter: direct derivation and implementation
Ángel F. García-Fernández, Jason L. Williams, Karl Granström +1
We provide a derivation of the Poisson multi-Bernoulli mixture (PMBM) filter for multi-target tracking with the standard point target measurements without using probability generat…
Multiple scan data association by convex variational inference
Jason L. Williams, Roslyn A. Lau
Data association, the reasoning over correspondence between targets and measurements, is a problem of fundamental importance in target tracking. Recently, belief propagation (BP) h…
An efficient, variational approximation of the best fitting multi-Bernoulli filter
Jason L. Williams
The joint probabilistic data association (JPDA) filter is a popular tracking methodology for problems involving well-spaced targets, but it is rarely applied in problems with close…
Approximate evaluation of marginal association probabilities with belief propagation
Jason L. Williams, Roslyn A. Lau
Data association, the problem of reasoning over correspondence between targets and measurements, is a fundamental problem in tracking. This paper presents a graphical model formula…
Hybrid Poisson and multi-Bernoulli filters
Jason L. Williams
The probability hypothesis density (PHD) and multi-target multi-Bernoulli (MeMBer) filters are two leading algorithms that have emerged from random finite sets (RFS). In this paper…
Marginal multi-Bernoulli filters: RFS derivation of MHT, JIPDA and association-based MeMBer
Jason L. Williams
Recent developments in random finite sets (RFSs) have yielded a variety of tracking methods that avoid data association. This paper derives a form of the full Bayes RFS filter and…
Graphical model approximations of random finite set filters
Jason L. Williams
Random finite sets (RFSs) has been a fruitful area of research in recent years, yielding new approximate filters such as the probability hypothesis density (PHD), cardinalised PHD…