Overview of Bayesian sequential Monte Carlo methods for group and extended object tracking

Lyudmila Mihaylova; Avishy Carmi; François Septier; Amadou Gning; Sze Kim Pang; Simon Godsill

doi:10.1016/j.dsp.2013.11.006

ScienceGate Book Chapters

JOURNAL ARTICLE

Overview of Bayesian sequential Monte Carlo methods for group and extended object tracking

Lyudmila Mihaylova Avishy Carmi François Septier Amadou Gning Sze Kim Pang Simon Godsill

Year: 2013 Journal: Digital Signal Processing Vol: 25 Pages: 1-16 Publisher: Elsevier BV

DOI: 10.1016/j.dsp.2013.11.006

Get Full-Text PDF Get Analytical Report

Keywords:

Markov chain Monte Carlo Computer science Monte Carlo method Group (periodic table) Curse of dimensionality Trajectory Tracking (education) Particle filter Random walk Bayesian probability Video tracking Object (grammar) Artificial intelligence Algorithm Computer vision Theoretical computer science Mathematics Statistics

Metrics

210

Cited By

21.22

FWCI (Field Weighted Citation Impact)

211

Refs

0.99

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Target Tracking and Data Fusion in Sensor Networks

Physical Sciences → Computer Science → Artificial Intelligence

Gaussian Processes and Bayesian Inference

Physical Sciences → Computer Science → Artificial Intelligence

Bayesian Methods and Mixture Models

Physical Sciences → Computer Science → Artificial Intelligence

Overview of Bayesian sequential Monte Carlo methods for group and extended object tracking

Metrics

Citation History

Topics

Related Documents

Sequential Monte Carlo framework for extended object tracking

Extended Object Tracking Using Monte Carlo Methods

Monte Carlo-Based Bayesian Group Object Tracking and Causal Reasoning

Bayesian Geosteering Using Sequential Monte Carlo Methods

Monte Carlo Methods and Bayesian Computation: Overview