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An adaptive and scalable multi-object tracker based on the non-homogeneous Poisson process
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 …
of data association uncertainty and heavy clutter, either with or without knowledge of the …
Radio-frequency tomography for passive indoor multitarget tracking
Radio-frequency (RF) tomography is the method of tracking targets using received signal-
strength (RSS) measurements for RF transmissions between multiple sensor nodes. When …
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
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 …
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
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 …
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
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 …
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
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 …
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
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 …
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
Benefitting from the advances in sensor nets, wireless communication, and embedded
systems, the cyber-physical system (CPS) has been implemented in many practical areas …
systems, the cyber-physical system (CPS) has been implemented in many practical areas …
Waste-free sequential monte carlo
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 …
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
In this paper we derive computationally-tractable approximations of the Probability
Hypothesis Density (PHD) and Cardinalized Probability Hypothesis Density (CPHD) filters …
Hypothesis Density (PHD) and Cardinalized Probability Hypothesis Density (CPHD) filters …