Multi-Target Tracking with Dependent Likelihood Structures in Labeled Random Finite Set Filters

@inproceedings{Chen2021MultiTargetTW,
  title={Multi-Target Tracking with Dependent Likelihood Structures in Labeled Random Finite Set Filters},
  author={Lingji Chen},
  booktitle={FUSION},
  year={2021}
}
  • Lingji Chen
  • Published in FUSION 8 August 2021
  • Computer Science
In multi-target tracking, a data association hypothesis assigns measurements to tracks, and the hypothesis likelihood (of the joint target-measurement associations) is used to compare among all hypotheses for truncation under a finite compute budget. It is often assumed however that an individual target-measurement association likelihood is independent of others, i.e., it remains the same in whichever hypothesis it belongs to. In the case of Track Oriented Multiple Hypothesis Tracking (TO-MHT… 

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