IS = { zkontrolovano 23 Jan 2014 },
  UPDATE  = { 2013-03-05 },
  AUTHOR =      {Zuz{\'a}nek, Petr and Zimmermann, Karel and Hlav{\'a}{\v c}, V{\'a}clav},
  title =       {Detection of {C}urvilinear {O}bjects in {A}erial {I}mages},
  year =        {2013},
  pages =       {9-15},
  book_pages =  {125},
  booktitle =   {CVWW 2013: Proceedings of the 18th Computer Vision Winter Workshop},
  publisher =   {Vienna University of Technology},
  address =     {Karlsplatz 13, Vienna, Austria},
  editor =      {Kropatsch, Walter G. and Ramachandran, Geetha and Torres, Fuensanta},
  month =       {February},
  isbn =        {978-3-200-02943-9},
  day =         {4-6},
  venue =       {Hernstein, Austria},
  annote =      {This paper introduces a general framework for
    autonomous detection of curvilinear objects in aerial images. Our
    contribution is two-fold. First, we designed simple yet efficient
    method, which sequentially prunes the space of possible
    curvilinear objects and thus reduces both the false negative rate
    detection and computational resources with respect to the
    exhaustive search methods. Second, our method can handle many
    types of curvilinear objects (e.g. roads, pipelines). We tested
    the method on our own dataset consisting of highway images. The
    produced data set is publicly available. We reached the 93.07 perc.
    overall accuracy.},
  keywords =    {Object detection, {R}idge detector, {G}entle {A}daboost classifier, {D}ynamic programming},
  project =     {TACR TE01020197, FP7-ICT-247870 NIFTi},