Vehicle Detection Based on Probability Hypothesis Density Filter [PDF]
Sensors, 2016 In the past decade, the developments of vehicle detection have been significantly improved. By utilizing cameras, vehicles can be detected in the Regions of Interest (ROI) in complex environments.
Feihu Zhang, Alois Knoll
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Particle Probability Hypothesis Density Filter Based on Pairwise Markov Chains [PDF]
Algorithms, 2019 Most multi-target tracking filters assume that one target and its observation follow a Hidden Markov Chain (HMC) model, but the implicit independence assumption of the HMC model is invalid in many practical applications, and a Pairwise Markov Chain (PMC)
Jiangyi Liu +3 more
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A general cardinalized probability hypothesis density filter
EURASIP Journal on Advances in Signal Processing, 2022 Based on random finite set, the probability hypothesis density (PHD) filter and the cardinalized PHD (CPHD) filter have been proposed for multitarget tracking as they are computational tractable.
Xinglin Shen +3 more
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Adaptive Collaborative Gaussian Mixture Probability Hypothesis Density Filter for Multi-Target Tracking [PDF]
Sensors, 2016 In this paper, an adaptive collaborative Gaussian Mixture Probability Hypothesis Density (ACo-GMPHD) filter is proposed for multi-target tracking with automatic track extraction. Based on the evolutionary difference between the persistent targets and the
Feng Yang +4 more
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Two Measurement Set Partitioning Algorithms for the Extended Target Probability Hypothesis Density Filter [PDF]
Sensors, 2019 The extended target probability hypothesis density (ET-PHD) filter cannot work well if the density of measurements varies from target to target, which is based on the measurement set partitioning algorithms employing the Mahalanobis distance between ...
Yulan Han, Chongzhao Han
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A Student’s t Mixture Probability Hypothesis Density Filter for Multi-Target Tracking with Outliers [PDF]
Sensors, 2018 In multi-target tracking, the outliers-corrupted process and measurement noises can reduce the performance of the probability hypothesis density (PHD) filter severely.
Zhuowei Liu +4 more
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Detection-Driven Gaussian Mixture Probability Hypothesis Density Multi-Target Tracker for Airborne Infrared Platforms [PDF]
SensorsRecent advancements in the unmanned aerial vehicle remote sensing field have highlighted the effectiveness of infrared sensors in detecting and tracking time-sensitive ground targets, particularly within the domain of early warning and surveillance ...
Mingyu Hong +5 more
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Multiple Vehicle Cooperative Localization with Spatial Registration Based on a Probability Hypothesis Density Filter [PDF]
Sensors, 2014 This paper studies the problem of multiple vehicle cooperative localization with spatial registration in the formulation of the probability hypothesis density (PHD) filter.
Feihu Zhang +2 more
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Journal of Algorithms & Computational Technology, 2021 The Gaussian inverse Wishart probability hypothesis density filter is a promising approach for tracking multiple extended targets. However, if targets are closely spaced and performing maneuvers, the performance of a Gaussian inverse Wishart probability ...
Peng Li +3 more
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Measurement + Control, 2021 Under the Gaussian noise assumption, the probability hypothesis density (PHD) filter represents a promising tool for tracking a group of moving targets with a time-varying number.
Weijun Xu
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