Distributed GM-CPHD Filter Based on Generalized Inverse Covariance Intersection
IEEE Access, 2021 In this paper, we propose a distributed Gaussian mixture cardinalized probability hypothesis density (GM-CPHD) filter based on generalized inverse covariance intersection that fuses multiple node information effectively for multi-target tracking ...
Woo Jung Park, Chan Gook Park
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Set Functions and Probability Distributions of a Finite Random Sets [PDF]
, 2018 This paper is the investigation of the probability distributions of a finite random set in which the set of random events are considered as a support of the finite random set.
Lukyanova, Natalia A. +2 more
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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
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Predecessors and successors in random mappings with exchangeable in-degrees [PDF]
, 2013 In this paper we characterise the distributions of the number of predecessors and of the number of successors of a given set of vertices, A, in the random mapping model, TnD^ (see Hansen and Jaworski (2008)), with exchangeable in-degree sequence (D^1,D^2,
Hansen, Jennie Charlotte +2 more
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Detection and Tracking of Moving Targets for Thermal Infrared Video Sequences
Sensors, 2018 The joint detection and tracking of multiple targets from raw thermal infrared (TIR) image observations plays a significant role in the video surveillance field, and it has extensive applied foreground and practical value. In this paper, a novel multiple-
Chenming Li, Wenguang Wang
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Cardinality Balanced Multi-Target Multi-Bernoulli Filter with Error Compensation
Sensors, 2016 The cardinality balanced multi-target multi-Bernoulli (CBMeMBer) filter developed recently has been proved an effective multi-target tracking (MTT) algorithm based on the random finite set (RFS) theory, and it can jointly estimate the number of targets ...
Xiangyu He, Guixi Liu
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Robust Poisson Multi-Bernoulli Filter With Unknown Clutter Rate
IEEE Access, 2019 In Bayesian multi-target tracking (MTT), knowledge of clutter intensity is required for effective multi-target state estimation. In this paper, we propose an online multi-target filter that can operate under background with unknown clutter intensity. Our
Weijian Si, Hongfan Zhu, Zhiyu Qu
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Multisensor Multi-Target Tracking Based on GM-PHD Using Out-Of-Sequence Measurements
Sensors, 2019 In this paper, we study the issue of out-of-sequence measurement (OOSM) in a multi-target scenario to improve tracking performance. The OOSM is very common in tracking systems, and it would result in performance degradation if we used it inappropriately.
Meiqin Liu +3 more
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Joint Detection and DOA Tracking with a Bernoulli Filter Based on Information Theoretic Criteria
Sensors, 2018 In this paper, we study the problem of the joint detection and direction-of-arrival (DOA) tracking of a single moving source which can randomly appear or disappear from the surveillance volume.
Guangpu Zhang +4 more
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Bayesian Multiple Target Filtering Using Random Finite Sets
, 2013 The random finite set (RFS) approach, introduced by Mahler as finite set statistics (FISST), is an elegant Bayesian formulation of multitarget filtering based on RFS theory. This chapter describes the RFS approach to multitarget tracking.
Vo, Ba Ngu +2 more
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