@InProceedings{Hurych-VS-ICCV2009,
  IS = { zkontrolovano 16 Oct 2009 },
  UPDATE  = { 2009-10-15 },
  author =       {Hurych, David and Svoboda, Tom{\'a}{\v s} and Trojanov{\' a}, Jana and US, Yadhunandan},
  title =        {Active Shape Model and Linear Predictors for Face Association Refinement},
  booktitle =    {The Ninth IEEE International Workshop on Visual Surveillance 2009, In conjunction
                  with the 12th IEEE International Conference on Computer Vision, 2009},
  book_pages  =  {2235},
  pages =        {1193-1200},
  year =         {2009},
  month =        {October},
  day =          {3},
  venue =        {Kyoto, Japan},
  authorship =   {40-30-25-5},
  project =      {1M0567, FP6-IST-027113, FP6-IST-027787},
  keywords =     {predictors, face, recognition, rectification},
  url = {ftp://cmp.felk.cvut.cz/pub/cmp/articles/hurycd1/hurych-VS2009.pdf},
  annote = {This paper summarizes results of face association
    experiments on real low resolution data from airport and the
    Labeled faces in the Wild (LFW) database. The objective of
    experiments is to evaluate different face alignment methods and
    their contribution to face association as such. The first
    alignment method used is Sequential Learnable Linear Predictor
    (SLLiP), originally developed for object tracking. The second
    method is well known face alignment method Active Shape Model
    (ASM). Both methods are compared versus face association without
    alignment. In case of high resolution LFW database the ASM rapidly
    increases the association results, on the other hand for real low
    resolution airport data the SLLiP method brought more improvement
    than ASM.},
  publisher = { IEEE Computer Society },
  address   = { Piscataway, USA },
  isbn      = { 978-1-4244-4441-0 },
  note      = { CD-ROM },
}