IS = { zkontrolovano 13 Jan 2012 },
  UPDATE  = { 2011-12-29 },
  author =      {Gron{\'a}t, Petr and Havlena, Michal and 
                 {\v S}ivic, Josef and Pajdla, Tom{\'a}{\v s}},
  title =       {Building Streetview Datasets for Place 
    Recognition and City Reconstruction},
  institution = {Center for Machine Perception, K13133 FEE
                 Czech Technical University},
  address =     {Prague, Czech Republic},
  year =        {2011},
  month =       {December},
  type =        {Research Report},
  number =      {CTU--CMP--2011--16},
  issn =        {1213-2365},
  pages =       {13},
  figures =     {5},
  authorship =  {25-25-25-25},
  psurl       = {[Gronat-TR-2011-16.pdf]},
  project =     {SGS10/190/OHK3/2T/13},
  annote = {Google Maps API combined with Street View images can serve
    as a powerful tool for place recognition or city reconstruction
    tasks. In this paper, we present a way how to build geotagged
    datasets of perspective views from Google Maps. Given the initial
    GPS coordi- nates, the algorithm can build a list of panoramas in
    a certain area, download corresponding panoramas, and generate
    perspective views. In more detail, each panorama on Google Maps
    Street View contains meta data from which the GPS location and the
    direction of the view can be extracted. Moreover, the information
    about the neighbouring panoramas can be obtained as well, hence, a
    list of panoramas cov- ering a certain area can be
    built. Downloading panoramas from the list and combining it with
    the meta data, each downloaded panorama is cut into a set of
    overlaping perspective views and stored while the camera GPS
    location, yaw, and pitch are coded in the filename of the
    perspective view. The geotagged database is subsequently used for
    place recognition and structure from motion 3D reconstruction.},
  keywords =    {geographically tagged database, visual localization, 
    google streetview},