An Efficient Labeled/Unlabeled Random Finite Set Algorithm for Multiobject Tracking [PDF]
IEEE Transactions on Aerospace and Electronic Systems, 2022 In this article, we propose an efficient random finite set (RFS)-based algorithm for multiobject tracking, in which the object states are modeled by a combination of a labeled multi-Bernoulli (LMB) RFS and a Poisson RFS.
Thomas Kropfreiter +2 more
exaly +2 more sources
Multiple vehicle cooperative localization under random finite set framework [PDF]
, 2013 —This paper presents a new multiple vehicle cooper-ative localization approach based on Random Finite Set (RFS) theory. Assuming vehicles are equipped with proprioceptive and exteroceptive sensors to localize the positions, a solution based on RFS ...
Feihu Zhang +2 more
exaly +2 more sources
Labeled Random Finite Sets and Multi-Object Conjugate Priors
IEEE Transactions on Signal Processing, 2013 The objective of multi-object estimation is to simultaneously estimate the number of objects and their states from a set of observations in the presence of data association uncertainty, detection uncertainty, false observations, and noise.
Ba-Ngu Võ
exaly +2 more sources
A Time–Frequency Masking Based Random Finite Set Particle Filtering Method for Multiple Acoustic Source Detection and Tracking [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2015 Considering that multiple talkers may appear simultaneously, a time-frequency (TF) masking based random finite set (RFS) particle filtering (PF) method is developed for multiple acoustic source detection and tracking.
Xionghu Zhong, James R Hopgood
exaly +2 more sources
IEEE Transactions on Signal Processing, 2006 -Speaker location estimation techniques based on time-difference-of-arrival (TDOA) measurements have attracted much attention recently. Many existing localization ideas assume that only one speaker is active at a time.
Wing-Kin Ma +2 more
exaly +1 more source
Explicit filtering equations for labelled random finite sets [PDF]
, 2015 We decompose a probability density function (PDF) of a labelled random finite set (RFS) into a probability mass function over a set of labels and a PDF on a vector-valued multitarget state given the labels. Using this decomposition, we write the Bayesian
García-Fernández, ÁF +5 more
core +1 more source
Track Classification for Random Finite Set Based Multi-Sensor Multi-Object Tracking
, 2023 The state-of-the-art of random finite set (RFS) based approaches for multi-sensor multi-object setups solve the classification and track estimation jointly in a Bayesian style.
Herrmann, Martin +4 more
core +1 more source
Random Finite Set Theory and Centralized Control of Large Collaborative Swarms
, 2021 Controlling large swarms of robotic agents presents many challenges, including, but not limited to, computational complexity due to a large number of agents, uncertainty in the functionality of each agent in the swarm, and uncertainty in the swarm’s ...
Zhu, Pingping +3 more
core +1 more source
Random finite set multi-target trackers: Stochastic geometry for space situational awareness
, 2015 © 2015 SPIE. This paper describes the recent development in the random finite set RFS paradigm in multi-target tracking. Over the last decade the Probability Hypothesis Density filter has become synonymous with the RFS approach.
Ba-Ngu Vo +3 more
core +1 more source
Poisson Multi-Bernoulli Mixture Trackers: Continuity Through Random Finite Sets of Trajectories. [PDF]
, 2018 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 Bernoulli components are generated on each new measurement as a part of the ...
Svensson, Lennart +9 more
core +2 more sources