Markov chain Monte Carlo data association for general multiple-target tracking problems

@article{Oh2004MarkovCM,
  title={Markov chain Monte Carlo data association for general multiple-target tracking problems},
  author={Songhwai Oh and Stuart Russell and S. V. S. SriHarsha Sastry},
  journal={2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)},
  year={2004},
  volume={1},
  pages={735-742 Vol.1}
}
In this paper, we consider the general multiple-target tracking problem in which an unknown number of targets appears and disappears at random times and the goal is to find the tracks of targets from noisy observations. We propose an efficient real-time algorithm that solves the data association problem and is capable of initiating and terminating a varying number of tracks. We take the data-oriented, combinatorial optimization approach to the data association problem but avoid the enumeration… CONTINUE READING
Highly Influential
This paper has highly influenced 20 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 301 citations. REVIEW CITATIONS
186 Citations
30 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 186 extracted citations

301 Citations

02040'07'10'13'16
Citations per Year
Semantic Scholar estimates that this publication has 301 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 30 references

Fortmann. Tracking and Data Association

  • T.E.Y. Bar-Shalom
  • Science and Engineering Series
  • 1988
Highly Influential
8 Excerpts

Efficient gating in data association with multivariate distributed states

  • J. B. Collins, J. K. Uhlmann
  • IEEE Trans . Aerospace and Electronic Systems
  • 2000

Similar Papers

Loading similar papers…