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Found 29 papers, 17 papers with code
Markov Chain Monte Carlo Data Association for Sets of Trajectories
This paper considers a batch solution to the multi-object tracking problem based on sets of trajectories.
Graph GOSPA metric: a metric to measure the discrepancy between graphs of different sizes
This paper proposes a metric to measure the dissimilarity between graphs that may have a different number of nodes.
Trajectory Poisson multi-Bernoulli mixture filter for traffic monitoring using a drone
This paper proposes a multi-object tracking (MOT) algorithm for traffic monitoring using a drone equipped with optical and thermal cameras.
The Trajectory PHD Filter for Coexisting Point and Extended Target Tracking
This paper develops a general trajectory probability hypothesis density (TPHD) filter, which uses a general density for target-generated measurements and is able to estimate trajectories of coexisting point and extended targets.
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.
A comparison between PMBM Bayesian track initiation and labelled RFS adaptive birth
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-Bernoulli mixture (PMBM) filter, with point-target models.
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.
Data-driven clustering and Bernoulli merging for the Poisson multi-Bernoulli mixture filter
This paper proposes a clustering and merging approach for the Poisson multi-Bernoulli mixture (PMBM) filter to lower its computational complexity and make it suitable for multiple target tracking with a high number of targets.
A time-weighted metric for sets of trajectories to assess multi-object tracking algorithms
This paper proposes a metric for sets of trajectories to evaluate multi-object tracking algorithms that includes time-weighted costs for localisation errors of properly detected targets, for false targets, missed targets and track switches.
An analysis on metric-driven multi-target sensor management: GOSPA versus OSPA
On the contrary, as a consequence of the spooky effect at a distance in optimal OSPA/UOSPA estimation, the optimal actions for different sensors using OSPA and UOSPA are entangled.
Continuous-discrete multiple target tracking with out-of-sequence measurements
When we receive an OOS measurement, the optimal Bayesian processing performs a retrodiction step that adds trajectory information at the OOS measurement time stamp followed by an update step.
Temporal Parallelization of Inference in Hidden Markov Models
This paper presents algorithms for parallelization of inference in hidden Markov models (HMMs).
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.
Poisson Multi-Bernoulli Mixtures for Sets of Trajectories
First, we show that, for the standard point target model, the PMBM density is conjugate also for sets of trajectories.
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.
Spooky effect in optimal OSPA estimation and how GOSPA solves it
In this paper, we show the spooky effect at a distance that arises in optimal estimation of multiple targets with the optimal sub-pattern assignment (OSPA) metric.
An Implementation of the Poisson Multi-Bernoulli Mixture Trajectory Filter via Dual Decomposition
This paper proposes an efficient implementation of the Poisson multi-Bernoulli mixture (PMBM) trajectory filter.
Trajectory PHD and CPHD filters
This paper presents the probability hypothesis density filter (PHD) and the cardinality PHD (CPHD) filter for sets of trajectories, which are referred to as the trajectory PHD (TPHD) and trajectory CPHD (TCPHD) filters.
Gaussian process classification using posterior linearisation
This paper proposes a new algorithm for Gaussian process classification based on posterior linearisation (PL).
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 target tracking based on sets of trajectories
We propose a solution of the multiple target tracking (MTT) problem based on sets of trajectories and the random finite set framework.
Trajectory probability hypothesis density filter
This paper presents the probability hypothesis density (PHD) filter for sets of trajectories: the trajectory probability density (TPHD) filter.
A metric on the space of finite sets of trajectories for evaluation of multi-target tracking algorithms
In this paper, we propose a metric on the space of finite sets of trajectories for assessing multi-target tracking algorithms in a mathematically sound way.
Generalized optimal sub-pattern assignment metric
This paper presents the generalized optimal sub-pattern assignment (GOSPA) metric on the space of finite sets of targets.
