Online Adaptive Hidden Markov Model for Multi-Tracker Fusion

  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},
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
Highly Cited
This paper has 25 citations. REVIEW CITATIONS
Recent Discussions
This paper has been referenced on Twitter 4 times over the past 90 days. VIEW TWEETS



Citations per Year

Citation Velocity: 9

Averaging 9 citations per year over the last 3 years.

Learn more about how we calculate this metric in our FAQ.