Memorias de investigación
Research Publications in journals:
On-road visual vehicle tracking using Markov chain Monte Carlo with metropolis sampling
Year:2012
Research Areas
  • Electronic technology and of the communications
Information
Abstract
In this study, a method for vehicle tracking through video analysis based on Markov chain Monte Carlo (MCMC) particle filtering with metropolis sampling is proposed. The method handles multiple targets with low computational requirements and is, therefore, ideally suited for advanced-driver assistance systems that involve real-time operation. The method exploits the removed perspective domain given by inverse perspective mapping (IPM) to define a fast and efficient likelihood model. Additionally, the method encompasses an interaction model using Markov Random Fields (MRF) that allows treatment of dependencies between the motions of targets. The proposed method is tested in highway sequences and compared to state-of-the-art methods for vehicle tracking, i.e., independent target tracking with Kalman filtering (KF) and joint tracking with particle filtering. The results showed fewer tracking failures using the proposed method.
International
Si
JCR
Si
Title
Int. Journal of Automotive Technology
ISBN
1229-9138
Impact factor JCR
Impact info
Volume
13
10.1007/s12239-012-0097-1
Journal number
6
From page
955
To page
961
Month
OCTUBRE
Ranking
Participants
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Tratamiento de Imágenes (GTI)