@InProceedings{ObdrzalekPerdochMatas08Dense,
  IS = { zkontrolovano 18 Jan 2009 },
  UPDATE  = { 2009-01-06 },
  author =       {{\v S}t{\v e}p{\' a}n Obdr{\v z}{\' a}lek and 
                  Michal Per{\v d}och and Ji{\v r}{\' i} Matas},
  title =        {Dense Linear-Time Correspondences for Tracking},
  year =         {2008},
  pages =        {8},
  booktitle =    {Proceedings of Workshop on Visual Localization
                  for Mobile Platforms held in conjunction
                  with CVPR 2008},
  book_pages =   {215},
  publisher =    {IEEE Computer Society},
  address =      {Piscataway, USA},
  isbn =         {978-1-4244-2339-2},
  issn =         {1063-6919},
  month =        {June},
  day =          {28},
  venue =        {Anchorage, USA},
  organization = {IEEE Computer Society},
  annote = {A novel method is proposed for the problem of
    frame-to-frame correspondence search in video sequences. The
    method, based on hashing of low-dimensional image descriptors,
    establishes dense correspondences and allows large motions.  All
    image pixels are considered for matching, the notion of interest
    points is reviewed. In our formulation, points of interest are
    those that can be reliably matched. Their saliency depends on
    properties of the chosen matching function and on actual image
    content.  Both computational time and memory requirements of the
    correspondence search are asymptoticaly linear in the number of
    image pixels, irrespective of correspondence density and of image
    content. All steps of the method are simple and allow for a
    hardware implementation.  Functionality is demonstrated on
    sequences taken from a vehicle moving in an urban environment.},
  keywords =     {correspondences, hashing, video},
  authorship =   {40-30-30},
  project =      {1M0567, HS Toyota},
  note =         {CD-ROM},
  www =          {http://cmp.felk.cvut.cz/~xobdrzal/publications/obdrzalek08DenseLinearTimeCorrespondencesForTracking.pdf},
}