Boosted Markov Chain Monte Carlo Data Association for Multiple Target Detection and Tracking

@article{Yu2006BoostedMC,
  title={Boosted Markov Chain Monte Carlo Data Association for Multiple Target Detection and Tracking},
  author={Qian Yu and Isaac Cohen and G{\'e}rard G. Medioni and Bo Wu},
  journal={18th International Conference on Pattern Recognition (ICPR'06)},
  year={2006},
  volume={2},
  pages={675-678}
}
In this paper, we present a probabilistic framework for automatic detection and tracking of objects. We address the data association problem by formulating the visual tracking as finding the best partition of a measurement graph containing all detected moving regions. In order to incorporate model information in tracking procedure, the posterior distribution is augmented with Adaboost image likelihood. We adopt a MRF-based interaction to model the inter-track exclusion. To avoid the exponential… CONTINUE READING

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