Real-Time Multi-Object Tracking using Random Finite Sets

Author

Reuter, Stephan ; Wilking, Benjamin ; Wiest, Juurgen ; Munz, Michael ; Dietmayer, Klaus

Author_Institution

Inst. of Meas., Control & Microtechnol., Ulm Univ., Ulm, Germany

Volume

49

Issue

4

fYear

2013

fDate

Oct-13

Firstpage

2666

Lastpage

2678

Abstract

The multi-object Bayes (MOB) filter uses random finite sets (RFSs) to represent a scene. A drawback of this filter is the computational complexity of the multi-object likelihood function. In this contribution, an approximation of the multi-object likelihood function is presented allowing for real-time implementation on a graphics processing unit using sequential Monte Carlo (SMC) methods. Additionally, a track extraction algorithm using clustering as well as an approach to determine the existence probability of each single object are proposed.

Keywords

Bayes methods; Monte Carlo methods; graphics processing units; object tracking; MOB filter; RFS; SMC method; graphics processing unit; multiobject Bayes filter; multiobject likelihood function; random finite set; real-time multiobject tracking; sequential Monte Carlo method; track extraction algorithm; Approximation methods; Atmospheric measurements; Filtering algorithms; Graphics processing units; Particle measurements; Real-time systems; Vectors;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/TAES.2013.6621844

Filename

6621844