@InProceedings{Jancosek-CVWW2008,
  IS = { zkontrolovano 30 Dec 2008 },
  UPDATE  = { 2008-05-02 },
  author =     {Jan{\v c}o{\v s}ek, Michal and Pajdla, Tomas},
  title =      {Effective seed generation for 3D reconstruction},
  booktitle =  {CVWW 2008: Proceedings of the 13th Computer Vision Winter Workshop},
  pages =      {83-90},
  year =       {2008},
  editor =     {Per{\v s}, Janez},
  month =      {February},
  day =        {4-6},
  publisher =  {Slovenian Pattern Recognition Society},
  address =    {Ljubljana, Slovenia},
  isbn =       {978-961-90901-4-5},
  book_pages = {130},
  venue =      {Moravske Toplice, Slovenia},
  project =    {MSMT Kontakt 9-06-17, FP6-IST-027787 DIRAC, MSM6840770038},
  authorship = {50-50},
  psurl =      {[Jancosek-CVWW2008.pdf]},
  annote = { Given a pair of calibrated cameras, we describe an
    effective seed construction method for 3D reconstruction which
    starts with initial estimates of seed position, improves them and
    computes good estimates normals. We formulate the seed
    construction as an optimization problem with a criterial function
    based on the similarity of reprojection of images on a
    hypothetical planar patch. We show that the criterial function is
    unimodal in certain area and all values in this area are greater
    than the values outside of this area.  The ability to estimate
    seeds depends on the surface texture.  Some methods evaluate the
    variance of intensities of seed texture to decide about the
    possibility of normal detection.  We show that there also exist
    nonhomogenous textures which are not discriminative. Our method is
    able to detect situations when the seed normal is not possible to
    detect e.g. the texture is not discriminative. The method found
    global optimum in 94% of our test data. We show in experiments,
    that our approach outperforms other most relevant approaches.},
  keywords = {3D reconstruction, Stereo, Multiview},
}