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Found 16 papers, 7 papers with code
Multiobject Tracking for Thresholded Cell Measurements
Our numerical results demonstrate the advantages of the proposed method that relies on thresholded cell measurements compared to the conventional multiobject tracking based on point measurements with and without AM.
Trajectory PMB Filters for Extended Object Tracking Using Belief Propagation
First, we present a PMBM conjugate prior on the posterior of sets of trajectories for a generalized measurement model, in which each object generates an independent set of measurements.
Multiple Object Trajectory Estimation Using Backward Simulation
In this paper, we first derive a general multi-trajectory backward smoothing equation based on random finite sets of trajectories.
A Scalable Track-Before-Detect Method With Poisson/Multi-Bernoulli Model
We propose a scalable track-before-detect (TBD) tracking method based on a Poisson/multi-Bernoulli model.
Scalable Detection and Tracking of Geometric Extended Objects
The proposed method dynamically introduces states of newly detected objects, efficiently performs probabilistic multiple-measurement to object association, and jointly infers the geometric shapes of objects.
A Poisson multi-Bernoulli mixture filter for coexisting point and extended targets
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 extended targets.
Backward Simulation for Sets of Trajectories
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 (unlabelled) filtering densities and the multitarget dynamic model.
Trajectory Poisson multi-Bernoulli filters
The filters are based on propagating a Poisson multi-Bernoulli (PMB) density on the corresponding set of trajectories through the filtering recursion.
Multi-Scan Implementation of the Trajectory Poisson Multi-Bernoulli Mixture Filter
A multi-scan trajectory PMBM filter and a multi-scan trajectory MBM filter, with the ability to correct past data association decisions to improve current decisions, are presented.
Signal Processing
Extended target Poisson multi-Bernoulli mixture trackers based on sets of trajectories
The Poisson multi-Bernoulli mixture (PMBM) is a multi-target distribution for which the prediction and update are closed.
Signal Processing
Gaussian implementation of the multi-Bernoulli mixture filter
This paper presents the Gaussian implementation of the multi-Bernoulli mixture (MBM) filter.
Poisson Multi-Bernoulli Approximations for Multiple Extended Object Filtering
The Poisson multi-Bernoulli mixture (PMBM) is a multi-object conjugate prior for the closed-form Bayes random finite sets filter.
Poisson multi-Bernoulli mixture filter: direct derivation and implementation
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 generating functionals or functional derivatives.
Multiple scan data association by convex variational inference
Data association, the reasoning over correspondence between targets and measurements, is a problem of fundamental importance in target tracking.
Approximate evaluation of marginal association probabilities with belief propagation
Data association, the problem of reasoning over correspondence between targets and measurements, is a fundamental problem in tracking.
Marginal multi-Bernoulli filters: RFS derivation of MHT, JIPDA and association-based MeMBer
Recent developments in random finite sets (RFSs) have yielded a variety of tracking methods that avoid data association.
