Results 31 to 40 of about 30,144 (206)
Particle filter implementation of the multi-Bernoulli filter for superpositional sensors [PDF]
2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2013 The multi-Bernoulli filter is a promising method for computationally efficient and accurate multi-target tracking. Computationally tractable approximations of the multi-Bernoulli filter equations for superpositional sensors were recently derived. In this paper we present a particle filter implementation of these approximate update filter equations.
Santosh Nannuru, Mark Coates
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Detection Optimized Labeled Multi-Bernoulli Algorithm for Visual Multi-target Tracking [PDF]
Jisuanji kexue yu tansuo, 2023 In a video multi-target tracking algorithm combining a detector with a tracker, the quality of detector affects the performance of the whole tracking algorithm.
JIANG Lingyun, YANG Jinlong
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Journal of Marine Science and Engineering, 2023 This paper proposes a centralized MTT method based on a state-of-the-art multi-sensor labeled multi-Bernoulli (LMB) filter in underwater multi-static networks with autonomous underwater vehicles (AUVs). The LMB filter can accurately extract the number of
Yuexing Zhang +5 more
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IEEE Access, 2018 The cardinality-balanced multi-target multi-Bernoulli (CBMeMBer) filter is a promising solution for multi-target tracking. However, the performance of the CBMeMBer filter will be degraded severely by outliers in the presence of heavy-tailed process noise
Mingjie Wang +3 more
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Multi-Objective Optimization Based Multi-Bernoulli Sensor Selection for Multi-Target Tracking
Sensors, 2019 This paper presents a novel multi-objective optimization based sensor selection method for multi-target tracking in sensor networks. The multi-target states are modelled as multi-Bernoulli random finite sets and the multi-Bernoulli filter is used to ...
Yun Zhu, Jun Wang, Shuang Liang
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Exact Closed-Form Multitarget Bayes Filters
Sensors, 2019 The finite-set statistics (FISST) foundational approach to multitarget tracking and information fusion has inspired work by dozens of research groups in at least 20 nations; and FISST publications have been cited tens of thousands of times.
Ronald Mahler
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The Adaptive Labeled Multi-Bernoulli Filter
CoRR, 2018 This paper proposes a new multi-Bernoulli filter called the Adaptive Labeled Multi-Bernoulli filter. It combines the relative strengths of the known Delta-Generalized Labeled Multi-Bernoulli and the Labeled Multi-Bernoulli filter. The proposed filter provides a more precise target tracking in critical situations, where the Labeled Multi-Bernoulli ...
Andreas Danzer +2 more
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Cardinalized balanced multi-Bernoulli filter SLAM method based on pose graph optimization
智能科学与技术学报, 2023 In the complex indoor environment, the traditional SLAM method based on random finite set theory has the problems of low robot pose accuracy and large amount of calculation.To solve these problems, a cardinalized balanced multi-Bernoulli filter SLAM ...
Zijing ZHANG, Fei ZHANG
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Bernoulli Particle/Box-Particle Filters for Detection and Tracking in the Presence of Triple Measurement Uncertainty [PDF]
, 2012 This work presents sequential Bayesian detection and estimation methods for nonlinear dynamic stochastic systems using measurements affected by three sources of uncertainty: stochastic, set-theoretic and data association uncertainty.
Gning, Amadou +5 more
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Visual multiple‐object tracking for unknown clutter rate
IET Computer Vision, 2018 In multi‐object tracking applications, model parameter tuning is a prerequisite for reliable performance. In particular, it is difficult to know statistics of false measurements due to various sensing conditions and changes in the field of views. In this
Du Yong Kim
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