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GBMOT

A gerneric graph-based multi-object tracking framework including several shortest path algorithms.

Citation

If you use this work please use the following bibtext entry:

@InProceedings{mothes2019one,
author={Mothes, Oliver and Denzler, Joachim},
editor={Cl{\'a}udio, Ana Paula
and Bechmann, Dominique
and Richard, Paul
and Yamaguchi, Takehiko
and Linsen, Lars
and Telea, Alexandru
and Imai, Francisco
and Tremeau, Alain},
title={One-Shot Learned Priors in Augmented Active Appearance Models for Anatomical Landmark Tracking},
booktitle={Computer Vision, Imaging and Computer Graphics -- Theory and Applications},
year={2019},
publisher={Springer International Publishing},
address={Cham},
pages={85--104},
isbn={978-3-030-12209-6}
}
@InProceedings{mothes2017anatomical,
  author = {Oliver Mothes and Joachim Denzler},
  title = {Anatomical Landmark Tracking by One-shot Learned Priors for Augmented Active Appearance Models},
  booktitle = {International Conference on Computer Vision Theory and Applications (VISAPP)},
  volume = {6},
  pages = {246-254},
  year = {2017},
  groups = {locomotion},
  isbn = {978-989-758-227-1},
  url = {http://www.scitepress.org/DigitalLibrary/PublicationsDetail.aspx?ID=/rbNlt9UhtA=&t=1},
}