IS = { zkontrolovano 07 Dec 2003 },
  UPDATE  = { 2003-10-09 },
  author =     {Kostkov{\'a}, Jana and {\v S}{\'a}ra, Radim},
  title =      {Stratified Dense Matching for Stereopsis in Complex Scenes},
  project =    {CTU 0306413, GACR 102/01/1371, MSM 212300013},
  authorship = {50-50},
  psurl = {
  year = {2003},
  pages = {339-348},
  booktitle =   {BMVC 2003: Proceedings of the 14th British
                 Machine Vision Conference},
  volume = {1},
  editor = {Harvey, Richard and Bangham, J. Andrew},
  isbn = {1-901725-23-5},
  book_pages = {813},
  publisher = {British Machine Vision Association},
  address = {London, UK},
  month = {September},
  day = {9--11},
  venue = {Norwich, UK},
  keywords = {stereo matching},
  annote = {Local joint image modeling in stereo matching brings more
   discriminable and stable matching features. Such features reduce
   the need for strong prior models (continuity) and thus algorithms
   that are less prone to false positive artefacts in general complex
   scenes can be applied.  One of the principal quality factors in
   area-based dense stereo is the matching window shape. As it cannot
   be selected without having any initial matching hypothesis we
   propose a stratified matching approach. The window adapts to
   high-correlation structures in disparity space found in
   pre-matching which is then followed by final matching. In a
   rigorous ground-truth experiment we show that Stratified Dense
   Matching is able to increase matching density 3x, matching
   accuracy 1.8x, and occlusion boundary detection 2x as
   compared to a fixed-size rectangular windows algorithm. Performance
   on real outdoor complex scenes is also evaluated.},