Group Object Structure and State Estimation With Evolving Networks and Monte Carlo Methods

@article{Gning2011GroupOS,
  title={Group Object Structure and State Estimation With Evolving Networks and Monte Carlo Methods},
  author={Amadou Gning and Lyudmila Mihaylova and Simon Maskell and Sze Kim Pang and Simon J. Godsill},
  journal={IEEE Transactions on Signal Processing},
  year={2011},
  volume={59},
  pages={1383-1396}
}
This paper proposes a technique for motion estimation of groups of targets based on evolving graph networks. The main novelty over alternative group tracking techniques stems from learning the network structure for the groups. Each node of the graph corresponds to a target within the group. The uncertainty of the group structure is estimated jointly with the group target states. New group structure evolving models are proposed for automatic graph structure initialization, incorporation of new… CONTINUE READING

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