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Covariance Tracking via Geometric Particle Filtering
EURASIP Journal on Advances in Signal Processing, 2010 Region covariance descriptor recently proposed has been approved robust and elegant to describe a region of interest, which has been applied to visual tracking.
Li Guangwei, Liu Yunpeng, Shi Zelin
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Brief paper: Freeway traffic estimation within particle filtering framework [PDF]
, 2007 This paper formulates the problem of real-time estimation of traffic state in freeway networks by means of the particle filtering framework. A particle filter (PF) is developed based on a recently proposed speed-extended cell-transmission model of ...
Mihaylova, Lyudmila +2 more
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Face Tracking and Recognition with the Use of Particle-Filtered Local Features
Journal of Telecommunications and Information Technology, 2023 A consistent particle filtering-based framework for the purpose of parallel face tracking and recognition from video sequences is proposed. A novel approach to defining randomized, particle filtering-driven local face features for the purpose of ...
Łukasz A. Stasiak, Andrzej Pacut
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An improved unbiased particle filter
Monte Carlo Methods and Applications, 2023 Abstract In this paper, we consider the filtering of partially observed multi-dimensional diffusion processes that are observed regularly at discrete times. We assume that, for numerical reasons, one has to time-discretize the diffusion process, which typically leads to filtering that is subject to discretization bias. The approach in [A.
Ajay Jasra +2 more
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Saturated particle filter [PDF]
Proceedings of the 2011 American Control Conference, 2011 In many practical applications the state variables are defined on a compact set of the state space. For estimating such variables constrained particle filters have been successfully applied to nonlinear systems. For the saturated system the measurement information can be used during the sampling procedure to obtain particles that approximate the true ...
Pawel Stano +2 more
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Particle Flow Gaussian Particle Filter
2022 25th International Conference on Information Fusion (FUSION), 2022 State estimation in non-linear models is performed by tracking the posterior distribution recursively. A plethora of algorithms have been proposed for this task. Among them, the Gaussian particle filter uses a weighted set of particles to construct a Gaussian approximation to the posterior.
Comandur, Karthik +2 more
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A particle filtering approach for joint detection/estimation of multipath effects on GPS measurements [PDF]
, 2007 Multipath propagation causes major impairments to Global Positioning System (GPS) based navigation. Multipath results in biased GPS measurements, hence inaccurate position estimates.
Giremus, Audrey +2 more
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CoRR, 2019 20 pages, 21 figures, https://www.youtube.com/watch?v ...
Ryuichi Ueda +2 more
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Probability hypothesis density filtering for real-time traffic state estimation and prediction [PDF]
, 2013 The probability hypothesis density (PHD) methodology is widely used by the research community for the purposes of multiple object tracking. This problem consists in the recursive state estimation of several targets by using the information coming from an
Mihaylova, Lyudmila +9 more
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A Probabilistic Perspective on Gaussian Filtering and Smoothing [PDF]
, 2010 15.07.13 KB. Ok to add report to Spiral.We present a general probabilistic perspective on Gaussian filtering and smoothing. This allows us to show that common approaches to Gaussian filtering/smoothing can be distinguished solely by their methods of ...
Deisenroth, MP, Ohlsson, H
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