IS = { zkontrolovano 13 Jan 2012 },
  UPDATE  = { 2011-10-18 },
  author =      {Melnikova, Olga and Prandi, Federico},
  title =       {3D Buildings Extraction from Aerial Images},
  year =        {2011},
  booktitle =   {ISPRS Hannover Workshop 2011: High-Resolution Earth Imaging for Geospatial Information},
  publisher =   {ISPRS Universitaet Hannover},
  address =     {Hannover, Germany},
  pages =       {25-29},
  book_pages =  {225},
  volume =      {XXXVIII-4/W19},
  month =       {June},
  day =         {14--17 },
  venue =       {Hannover, Germany},
  annote =      {This paper introduces a semi-automatic method for
    buildings extraction through multiple-view aerial image
    analysis. The advantage of the used semi-automatic approach is
    that it allows processing of each building individually finding
    the parameters of buildings features extraction more precisely for
    each area. On the early stage the presented technique uses an
    extraction of line segments that is done only inside of areas
    specified manually. The rooftop hypothesis is used further to
    determine a subset of quadrangles, which could form building roofs
    from a set of extracted lines and corners obtained on the previous
    stage. After collecting of all potential roof shapes in all images
    overlaps, the epipolar geometry is applied to find matching
    between images. This allows to make an accurate selection of
    building roofs removing false-positive ones and to identify their
    global 3D coordinates given camera internal parameters and
    coordinates. The last step of the image matching is based on
    geometrical constraints in contrast to traditional
    correlation. The correlation is applied only in some highly
    restricted areas in order to find coordinates more precisely, in
    such a way significantly reducing processing time of the
    algorithm. The algorithm has been tested on a set of Milans aerial
    images and shows highly accurate results.},
  keywords =    {Buildings Detection, Rooftop Hypothesis, 
                 Image Matching, Features Extraction},
  project =     {FP7-ICT-247022 MASH, SGS10/069/OHK3/1T/13},
  psurl = {http://www.isprs.org/proceedings/XXXVIII/4-W19/paper/Contribution113.pdf },
  note =        {Electronic publication},