Bayesian Networks and Probabilistic Data Association Methods for Multi-Object Tracking: Application to Road Safety

This paper presents a Bayesian network-based approach to multisensor multitarget detection and tracking problem. The aim here is to propose an improvement of the probabilistic data association approach that takes into account contextual information about the scene. This information is modeled by a B...

Full description

Saved in:
Bibliographic Details
Main Authors: Jida, B., Lherbier, R., Wahl, M., Noyer, J.-C.
Format: Conference Proceeding
Language:English
Subjects:
Bayesian methods
Bayesian Networks
dynamic estimation
Laser radar
Multi-object tracking
Object detection
probabilistic data association
Radar detection
Radar tracking
Road safety
Road vehicles
Target tracking
Vehicle dynamics
Vehicle safety
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper presents a Bayesian network-based approach to multisensor multitarget detection and tracking problem. The aim here is to propose an improvement of the probabilistic data association approach that takes into account contextual information about the scene. This information is modeled by a Bayesian network that allows a dynamic estimation of the detection probability of the PDA. Our approach is then applied to synthetic data from scanning radar that is mounted on a moving vehicle. The aim is to detect the surrounding objects and track them through the sequence.
DOI:10.1109/ICTTA.2008.4529961