@Inproceedings{Vojir_LNCS2014,
  IS = { zkontrolovano 13 Jan 2014 },
  UPDATE  = { 2014-01-06 },
    keywords={tracking},
    project = {GACR P103/12/G084, SGS13/142/OHK3/2T/13},
    annote = {The paper presents contributions to the design of the
                  Flock of Trackers (FoT). The FoT estimates the pose
                  of the tracked object by robustly combining
                  displacement estimates from a subset of local
                  trackers that cover the object and has been. The
                  enhancements of the Flock of Trackers are: (i) new
                  reliability predictors for the local trackers - the
                  Neighbourhood consistency predictor and the Markov
                  predictor, (ii) new rules for combining the
                  predictions and (iii) introduction of a RANSAC-based
                  estimator of object motion. The enhanced FoT was
                  extensively tested on 62 sequences.Most of the
                  sequences are standard and used in the
                  literature. The improved FoT showed performance
                  superior to the reference method. For all 62
                  sequences, the ground truth is made publicly
                  available.},
    year={2014},
    month={January},
    isbn={978-3-642-44906-2},
    booktitle={Registration and Recognition in Images and Videos},
    volume={532},
    series={Studies in Computational Intelligence},
    editor={Cipolla, Roberto and Battiato, Sebastiano and Farinella, Giovanni Maria},
    doi={10.1007/978-3-642-44907-9=6},
    title={The Enhanced Flock of Trackers},
    url={http://dx.doi.org/10.1007/978-3-642-44907-9_6},
    publisher={Springer},
    author={Voj{\'\i}{\v r}, Tom{\' a}{\v s} and Matas, Ji{\v r}{\'\i}},
    book_pages =  {281},
    address =     {New York, US},
    pages={113-136},
}