Wang-Landau Monte Carlo-Based Tracking Methods for Abrupt Motions

@article{Kwon2013WangLandauMC,
  title={Wang-Landau Monte Carlo-Based Tracking Methods for Abrupt Motions},
  author={Junseok Kwon and Kyoung Mu Lee},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2013},
  volume={35},
  pages={1011-1024}
}
We propose a novel tracking algorithm based on the Wang-Landau Monte Carlo (WLMC) sampling method for dealing with abrupt motions efficiently. Abrupt motions cause conventional tracking methods to fail because they violate the motion smoothness constraint. To address this problem, we introduce the Wang-Landau sampling method and integrate it into a Markov Chain Monte Carlo (MCMC)-based tracking framework. By employing the novel density-of-states term estimated by the Wang-Landau sampling method… CONTINUE READING

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