Results 41 to 50 of about 513,541 (222)
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
openaire +4 more sources
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
doaj +1 more source
Multiple Maneuvering Targets Tracking Using MM-CBMeMBer Filter
Leida xuebao, 2012 The existing multiple model hypothesis density filter can estimate the number and state of maneuvering targets at the same time. Yet its Sequential Monte Carlo (SMC) implementation involves clustering algorithm, which is unstable and time consuming, and ...
Xiong Bo, Gan Lu
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IEEE Access, 2022 The partial-update Kalman filter (PKF) is an extension of the Schmidt Kalman filter, which can improve the capabilities of the conventional extended Kalman filter for handling model uncertainties and nonlinearities.
Ajay Pratap Yadav +3 more
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AlgorithmsThe Poisson multi-Bernoulli mixture (PMBM) filter is an effective approach for multi-object tracking in complex scenarios. However, its performance deteriorates when surviving objects spawn, as the PMBM filter only classifies detected objects as either ...
Youpeng Sun +5 more
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Box-Particle Labeled Multi-Bernoulli Filter for Multiple Extended Target Tracking [PDF]
Radioengineering, 2016 This paper focuses on real-time tracking of multiple extended targets in clutter based on labeled multi-Bernoulli filter. To address this problem, a novel approach is proposed within the recently presented box-particle framework.
M. Li, Z. Lin, W. An, Y. Zhou
doaj
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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Extended Target Marginal Distribution Poisson Multi-Bernoulli Mixture Filter
Sensors, 2020 The existence of clutter, unknown measurement sources, unknown number of targets, and undetected probability are problems for multi-extended target tracking, to address these problems; this paper proposes a gamma-Gaussian-inverse Wishart (GGIW ...
Haocui Du, Weixin Xie
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Adaptive δ-Generalized Labeled Multi-Bernoulli Filter for Multi-Object Detection and Tracking
IEEE Access, 2021 The δ-generalized labeled multi-Bernoulli (δ-GLMB) filter is an efficient approach for multiobject tracking in case of high clutter density and low detection probability.
Zong-Xiang Liu +3 more
doaj +1 more source
Advanced Materials, EarlyView.We present elastomeric three‐dimensional (3D) microstructures fabricated via two‐photon polymerization (2PP) and post‐processed through wet etching, for quantifying nanonewton (nN)‐scale forces applied by healthy and diseased neural cells. The mechanically characterized free‐standing beam architectures enable measurement of traction forces of ...
Pieter F. J. van Altena +7 more
wiley +1 more source