IS = { zkontrolovano 28 Jan 2010 },
  UPDATE  = { 2009-09-21 },
  author =      {Havlena, Michal and Torii, Akihiko and 
                 Knopp, Jan and Pajdla, Tom{\'a}{\v s}},
  title =       {Randomized Structure from Motion Based on 
                 Atomic {3D} Models from Camera Triplets},
  year =        {2009},
  pages =       {2874-2881},
  booktitle =   {CVPR 2009: Proceedings of the 2009 IEEE Computer
                 Society Conference on Computer Vision and Pattern Recognition},
  publisher =   {Omnipress},
  address =     {Madison, USA},
  isbn =        {978-1-4244-3991-1},
  issn =        {1063-6919},
  book_pages =  {3000},
  month =       {June},
  day =         {20-25},
  venue =       {Miami Beach, USA},
  organization ={IEEE Computer Society},
  annote = {This paper presents a new efficient technique for
    large-scale structure from motion from unordered data sets. We
    avoid costly computation of all pairwise matches and geometries by
    sampling pairs of images using the pairwise similarity scores
    based on the detected occurrences of visual words leading to a
    significant speedup.  Furthermore, atomic 3D models reconstructed
    from camera triplets are used as the seeds which form the final
    large-scale 3D model when merged together. Using three views
    instead of two allows us to reveal most of the outliers of
    pairwise geometries at an early stage of the process hindering
    them from derogating the quality of the resulting 3D structure at
    later stages. The accuracy of the proposed technique is shown on a
    set of 64 images where the result of the exhaustive technique is
    known. Scalability is demonstrated on a landmark reconstruction
    from hundreds of images.},
  keywords =    {Structure from Motion, Unordered Data Sets, Omnidirectional Vision},
  prestige =    {important},
  authorship =  {30-30-10-30},
  note =        {CD-ROM},
  project =     {FP6-IST-027787 DIRAC, GACR 201/07/1136, MSM6840770038, CTU0921413},
  psurl =       {[10.1109/CVPRW.2009.5206677.pdf]},