Multiple Hypothesis Tracking Revisited

@article{Kim2015MultipleHT,
  title={Multiple Hypothesis Tracking Revisited},
  author={Chanho Kim and Fuxin Li and Arridhana Ciptadi and James M. Rehg},
  journal={2015 IEEE International Conference on Computer Vision (ICCV)},
  year={2015},
  pages={4696-4704}
}
This paper revisits the classical multiple hypotheses tracking (MHT) algorithm in a tracking-by-detection framework. The success of MHT largely depends on the ability to maintain a small list of potential hypotheses, which can be facilitated with the accurate object detectors that are currently available. We demonstrate that a classical MHT implementation from the 90's can come surprisingly close to the performance of state-of-the-art methods on standard benchmark datasets. In order to further… 

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