Paper Info
Title
Joint Tracking and Ground Plane Estimation.
Abstract
We propose a novel framework that jointly estimates the ground plane and a target's motion trajectory. This results in improvements for both. Estimating their joint posterior is based on Particle Markov Chain Monte Carlo (Particle MCMC). In Particle MCMC, the best target state is inferred by a particle filter and the best ground plane is obtained by MCMC. Compared with conventional sampling method...
Year
DOI
Venue
2016
10.1109/LSP.2016.2601085
IEEE Signal Processing Letters
Keywords
Field
DocType
Estimation,Target tracking,Particle filters,Proposals,Trajectory,Visualization,Signal processing algorithms
Mathematical optimization,Markov chain Monte Carlo,Visualization,Sampling error,Particle filter,Ground plane,Sampling (statistics),Mathematics,Particle,Trajectory
Journal
Volume
Issue
ISSN
23
11
1070-9908
Citations 
PageRank 
References 
5
0.48
14
Authors
3
Name
Order
Citations
PageRank
Junseok Kwon159538.74
Ralf Dragon2181.93
Luc Van Gool3275661819.51