@inproceedings{Lebeda-VOT2013,
  title     = {Long-Term Tracking Through Failure Cases},
  booktitle = {ICCV workshop on Visual Object Tracking Challenge},
  author    = {Lebeda, Karel and Hadfield, Simon and Matas, Ji{\v r}{\' \i} and Bowden, Richard},
  pages		= {153--160},
  year      = {2013},
  month     = {December},
  day       = {2},
  venue     = {Sydney, Australia},
  psurl     = {http://cvssp.org/Personal/KarelLebeda/papers/VOT2013.pdf},
  annote    = {Long term tracking of an object, given only a single
				instance in an initial frame, remains an open problem. We
				propose a visual tracking algorithm, robust to many of the
				difficulties which often occur in real-world scenes.
				Correspondences of edge-based features are used, to overcome
				the reliance on the texture of the tracked object and improve
				invariance to lighting. Furthermore we address long-term
				stability, enabling the tracker to recover from drift and to
				provide redetection following object disappearance or
				occlusion. The two-module principle is similar to the
				successful state-of-the-art long-term TLD tracker, however our
				approach extends to cases of low-textured objects.},
  keywords  = {computer vision, visual tracking, long-term tracking, low texture, edge, line correspondence},
  doi		= {10.1109/ICCVW.2013.26},
  prestige  = {international},
  project   = {GACR P103/12/G084, EPSRC EP/I011811/1},
  status    = {published}
}