@InProceedings{Tylecek-CVWW-2009,
  IS = { zkontrolovano 28 Jan 2010 },
  UPDATE  = { 2009-07-27 },
  author =      {Tyle{\v c}ek, Radim and {\v S}{\'a}ra, Radim},
  title =       {Depth Map Fusion with Camera Position Refinement},
  year =        {2009},
  pages =       {59-66},
  book_pages =  {188},
  booktitle =   {CVWW '09: Computer Vision Winter Workshop 2009},
  editor =	 {Ion, A. and Kropatsch, Walter G.},
  publisher =	 {PRIP TU Wien},
  address =	 {Wien, Austria},
  month =	 {February},
  day =		 {4-6},
  venue =	 {Eibiswald, Austria},
  annote = {We present a novel algorithm for image-based surface
    reconstruction from a set of calibrated images.  The problem is
    formulated in Bayesian framework, where estimates of depth and
    visibility in a set of selected cameras are iteratively improved.
    The core of the algorithm is the minimisation of overall geometric
    L_2 error between measured 3D points and the depth estimates.
    In the visibility estimation task, the algorithm aims at outlier
    detection and noise suppression, as both types of errors are often
    present in the stereo output.  The geometrical formulation allows
    for simultaneous refinement of the external camera parameters,
    which is an essential step for obtaining accurate results even
    when the calibration is not precisely known.  We show that the
    results obtained with our method are comparable to other
    state-of-the-art techniques. },
  keywords =	 {computer vision, surface reconstruction},
  authorship =	 {50-50},
  project =	 {1ET101210406},
  isbn = {978-3-200-01390-2},
}