Multiple Target Tracking Using Spatio-Temporal Markov Chain Monte Carlo Data Association

2007 ◽  
Author(s):  
Qian Yu ◽  
Gerard Medioni ◽  
Isaac Cohen
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Target Tracking ◽  
Data Association ◽  
Multiple Target Tracking ◽  
Multiple Target ◽  
Monte Carlo Data ◽  
Spatio Temporal

scholarly journals Gating Techniques for Rao-Blackwellized Monte Carlo Data Association Filter

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Yazhao Wang ◽  
Peini Zhang
Keyword(s):  
Monte Carlo ◽  
Data Association ◽  
Multiple Target Tracking ◽  
Time Cost ◽  
Multiple Target ◽  
Monte Carlo Data ◽  
Tracking Ability ◽  
Obvious Benefit ◽  
Measurement Uncertainties ◽  
Simulation Results

This paper studies the Rao-Blackwellized Monte Carlo data association (RBMCDA) filter for multiple target tracking. The elliptical gating strategies are redesigned and incorporated into the framework of the RBMCDA filter. The obvious benefit is the reduction of the time cost because the data association procedure can be carried out with less validated measurements. In addition, the overlapped parts of the neighboring validation regions are divided into several separated subregions according to the possible origins of the validated measurements. In these subregions, the measurement uncertainties can be taken into account more reasonably than those of the simple elliptical gate. This would help to achieve higher tracking ability of the RBMCDA algorithm by a better association prior approximation. Simulation results are provided to show the effectiveness of the proposed gating techniques.

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