Online Adaptive Hidden Markov Model for Multi-Tracker Fusion

@article{Vojr2016OnlineAH,
  title={Online Adaptive Hidden Markov Model for Multi-Tracker Fusion},
  author={Tom{\'a}s Voj{\'i}r and Jiri Matas and Jana Noskova},
  journal={Computer Vision and Image Understanding},
  year={2016},
  volume={153},
  pages={109-119}
}
In this paper, we propose a novel method for visual object tracking called HMMTxD. The method fuses observations from complementary out-of-the box trackers and a detector by utilizing a hidden Markov model whose latent states correspond to a binary vector expressing the failure of individual trackers. The Markov model is trained in an unsupervised way, relying on an online learned detector to provide a source of tracker-independent information for a modified BaumWelch algorithm that updates the… CONTINUE READING
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