IS = { zkontrolovano 02 Feb 2010 },
  UPDATE  = { 2009-12-29 },
  author =       {Timofte, Radu and Zimmermann, Karel and Van Gool, Luc},
  title =        {Multi-view traffic sign detection, recognition, and 3D localisation},
  booktitle =    {Ninth IEEE Computer Society Workshop on Application of
                  Computer Vision},
  authorship =   {34-33-33},
  project =      {URBAN},
  venue  =       {Snowbird, USA},
  pages =        {69-76},
  publisher =    {IEEE Computer Society Press},
  address  =     {New York, USA},
  keywords =     {traffic signs, 3D mapping},
  month =        {December},
  day =          {7-9},
  year =         {2009},
  isbn =         {978-1-4244-5496-9},
  book_pages =   {495},
  annote = {Several applications require information about street
    furniture. Part of the task is to survey all traffic signs. This
    has to be done for millions of km of road, and the exercise needs
    to be repeated every so often. A van with 8 roofmounted cameras
    drove through the streets and took images every meter. The paper
    proposes a pipeline for the efficient detection and recognition of
    traffic signs. The task is challenging, as illumination conditions
    change regularly, occlusions are frequent, 3D positions and
    orientations vary substantially, and the actual signs are far less
    similar among equal types than one might expect. We combine 2D and
    3D techniques to improve results beyond the state-of-theart, which
    is still very much preoccupied with single view analysis.},