Journal ArticleDOI
Novel approach to nonlinear/non-Gaussian Bayesian state estimation
Neil Gordon,David Salmond,Adrian F. M. Smith +2 more
- Vol. 140, Iss: 2, pp 107-113
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TLDR
An algorithm, the bootstrap filter, is proposed for implementing recursive Bayesian filters, represented as a set of random samples, which are updated and propagated by the algorithm.Abstract:
An algorithm, the bootstrap filter, is proposed for implementing recursive Bayesian filters. The required density of the state vector is represented as a set of random samples, which are updated and propagated by the algorithm. The method is not restricted by assumptions of linear- ity or Gaussian noise: it may be applied to any state transition or measurement model. A simula- tion example of the bearings only tracking problem is presented. This simulation includes schemes for improving the efficiency of the basic algorithm. For this example, the performance of the bootstrap filter is greatly superior to the standard extended Kalman filter.read more
Citations
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Journal ArticleDOI
Prognostic modelling options for remaining useful life estimation by industry
TL;DR: Business issues that need to be considered when selecting an appropriate modelling approach for trial are discussed and classification tables and process flow diagrams are presented to assist industry and research personnel select appropriate prognostic models for predicting the remaining useful life of engineering assets within their specific business environment.
Book ChapterDOI
Stochastic Tracking of 3D Human Figures Using 2D Image Motion
TL;DR: A probabilistic method for tracking 3D articulated human figures in monocular image sequences that relies only on a frame-to-frame assumption of brightness constancy and hence is able to track people under changing viewpoints, in grayscale image sequences, and with complex unknown backgrounds.
Book ChapterDOI
ICONDENSATION: Unifying Low-Level and High-Level Tracking in a Stochastic Framework
Michael Isard,Andrew Blake +1 more
TL;DR: A new technique to combine low- and high-level information in a consistent probabilistic framework is presented, using the statistical technique of importance sampling combined with the Condensation algorithm, and a hand tracker is demonstrated which combines colour blob-tracking with a contour model.
Journal ArticleDOI
Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using the particle filter
TL;DR: Particle filters are introduced as a sequential Bayesian filtering having features that represent the full probability distribution of predictive uncertainties, and their applicability to the approximation of the posterior distribution of parameters is investigated.
Journal ArticleDOI
Online Multiperson Tracking-by-Detection from a Single, Uncalibrated Camera
TL;DR: This paper proposes a novel approach for multiperson tracking-by-detection in a particle filtering framework that detects and tracks a large number of dynamically moving people in complex scenes with occlusions, requires no camera or ground plane calibration, and only makes use of information from the past.
References
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BookDOI
Density estimation for statistics and data analysis
TL;DR: The Kernel Method for Multivariate Data: Three Important Methods and Density Estimation in Action.
Book
Stochastic Processes and Filtering Theory
TL;DR: In this paper, a unified treatment of linear and nonlinear filtering theory for engineers is presented, with sufficient emphasis on applications to enable the reader to use the theory for engineering problems.
Journal ArticleDOI
Nonlinear Bayesian estimation using Gaussian sum approximations
D. Alspach,H. Sorenson +1 more
TL;DR: In this paper an approximation that permits the explicit calculation of the a posteriori density from the Bayesian recursion relations is discussed and applied to the solution of the nonlinear filtering problem.
Journal Article
Bayesian statistics without tears: A sampling-resampling perspective
TL;DR: In this article, a sampling-resampling perspective on Bayesian inference is presented, which has both pedagogic appeal and suggests easily implemented calculation strategies, such as sampling-based methods.