Results 41 to 50 of about 6,182,412 (149)
GLMB Tracker with Partial Smoothing
Sensors, 2019 In this paper, we introduce a tracking algorithm based on labeled Random Finite Sets (RFS) and Rauch–Tung–Striebel (RTS) smoother via a Generalized Labeled Multi-Bernoulli (GLMB) multi-scan estimator to track multiple objects in a wide range of tracking ...
Tran Thien Dat Nguyen, Du Yong Kim
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A random finite set conjugate prior and application to multi-target tracking
, 2011 The objective of multi-object estimation is to simultaneously estimate the number of objects and their states from a set of observations in the presence of data association uncertainty, detection uncertainty, false observations and noise. This estimation
Ba Tuong Vo (20066427) +1 more
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Receding Horizon Estimation for Multi-Target Tracking via Random Finite Set Approach
, 2018 © 2018 ISIF This paper proposes a robust multi-target tracking algorithm for uncertainty in dynamic motion modeling. To address this issue, the multi-target tracking problem is formulated under random finite set (RFS) framework with finite length memory ...
Du Yong Kim (13432683)
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Sensors, 2019 Under realistic environmental conditions, heuristic-based data association and map management routines often result in divergent map and trajectory estimates in robotic Simultaneous Localization And Mapping (SLAM). To address these issues, SLAM solutions
Diluka Moratuwage +2 more
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Joint PHD Filter and Hungarian Assignment Algorithm for Multitarget Tracking in Low Signal-to-Noise Ratio [PDF]
Radioengineering, 2023 Multitarget tracking (MTT) for image processing in low signal-to-noise ratio (SNR) is difficult and computationally expensive because the distinction between the target and the background is small. Among the current MTT algorithms, Random Finite Set (RFS)
S. Xiao +4 more
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Multiobject Tracking with Track Continuity: An Efficient Random Finite Set Based Algorithm
, 2018 We propose a random finite set (RFS) based algorithm for tracking multiple objects while maintaining track continuity. In our approach, the object states are modeled by a combination of a labeled multi-Bernoulli (LMB) RFS and a Poisson RFS.
Thomas Kropfreiter +3 more
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Random Finite Set Theory and Centralized Control of Large Collaborative Swarms
, 2021 Controlling large swarms of robotic agents presents many challenges, including, but not limited to, computational complexity due to a large number of agents, uncertainty in the functionality of each agent in the swarm, and uncertainty in the swarm’s ...
Zhu, Pingping +3 more
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Remote SensingNetwork-group targets are a set of objectives that adhere to a shared communication protocol, perform common tasks, and exhibit relatively coordinated movements. Typically, network-group targets emit radar and communication signals.
Ximeng Zhang +5 more
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Constrained Multi-Sensor Control Using a Multi-Target MSE Bound and a δ-GLMB Filter
Sensors, 2018 The existing multi-sensor control algorithms for multi-target tracking (MTT) within the random finite set (RFS) framework are all based on the distributed processing architecture, so the rule of generalized covariance intersection (GCI) has to be used to
Feng Lian +3 more
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A labeled random finite set spawning model
, 2017 © 2017 IEEE. Previous labeled random finite set filter developments use a target motion model that only accounts for survival and birth. While such a model provides the means for a multi-target tracking filter such as the Generalized Labeled Multi ...
Ba Tuong Vo (20066427) +3 more
core +2 more sources