An adaptive and scalable multi-object tracker based on the non-homogeneous Poisson process

Q Li, R Gan, J Liang, SJ Godsill - IEEE Transactions on Signal …, 2023‏ - ieeexplore.ieee.org
This paper proposes a new adaptive framework for tracking multiple objects in the presence
of data association uncertainty and heavy clutter, either with or without knowledge of the …

Radio-frequency tomography for passive indoor multitarget tracking

S Nannuru, Y Li, Y Zeng, M Coates… - IEEE Transactions on …, 2012‏ - ieeexplore.ieee.org
Radio-frequency (RF) tomography is the method of tracking targets using received signal-
strength (RSS) measurements for RF transmissions between multiple sensor nodes. When …

Langevin and Hamiltonian based sequential MCMC for efficient Bayesian filtering in high-dimensional spaces

F Septier, GW Peters - IEEE Journal of selected topics in signal …, 2015‏ - ieeexplore.ieee.org
Nonlinear non-Gaussian state-space models arise in numerous applications in statistics and
signal processing. In this context, one of the most successful and popular approximation …

Multi-target tracking and occlusion handling with learned variational Bayesian clusters and a social force model

A Ur-Rehman, SM Naqvi, L Mihaylova… - IEEE Transactions …, 2015‏ - ieeexplore.ieee.org
This paper considers the problem of multiple human target tracking in a sequence of video
data. A solution is proposed which is able to deal with the challenges of a varying number of …

Implementation of the Daum-Huang exact-flow particle filter

T Ding, MJ Coates - 2012 IEEE Statistical Signal Processing …, 2012‏ - ieeexplore.ieee.org
Several versions of the Daum-Huang (DH) filter have been introduced recently to address
the task of discrete-time nonlinear filtering. The filters propagate a particle set over time to …

Sequential dynamic leadership inference using Bayesian Monte Carlo methods

Q Li, BI Ahmad, SJ Godsill - IEEE Transactions on Aerospace …, 2021‏ - ieeexplore.ieee.org
Hierarchy and leadership interactions commonly occur in animal groups, crowds of people,
and in vehicle motions. Such interactions are often affected by one or more individuals who …

A multi-target track-before-detect particle filter using superpositional data in non-Gaussian noise

N Ito, S Godsill - IEEE Signal Processing Letters, 2020‏ - ieeexplore.ieee.org
We propose a particle filter (PF) for tracking time-varying states (eg, position, velocity) of
multiple targets jointly from superpositional data, which depend on the sum of all target …

A cyber-physical system-based velocity-profile prediction method and case study of application in plug-in hybrid electric vehicle

Y Zhang, L Chu, Y Ou, C Guo, Y Liu… - IEEE transactions on …, 2019‏ - ieeexplore.ieee.org
Benefitting from the advances in sensor nets, wireless communication, and embedded
systems, the cyber-physical system (CPS) has been implemented in many practical areas …

Waste-free sequential monte carlo

HD Dau, N Chopin - Journal of the Royal Statistical Society …, 2022‏ - academic.oup.com
A standard way to move particles in a sequential Monte Carlo (SMC) sampler is to apply
several steps of a Markov chain Monte Carlo (MCMC) kernel. Unfortunately, it is not clear …

Computationally-tractable approximate PHD and CPHD filters for superpositional sensors

S Nannuru, M Coates, R Mahler - IEEE Journal of Selected …, 2013‏ - ieeexplore.ieee.org
In this paper we derive computationally-tractable approximations of the Probability
Hypothesis Density (PHD) and Cardinalized Probability Hypothesis Density (CPHD) filters …