IS = { zkontrolovano 02 Dec 2005 },
  UPDATE  = { 2005-07-18 },
 key =         {Cech-SCIA-2005},
 author   = { {\v C}ech, Jan and {\v S}{\'a}ra, Radim },
 title =       {Complex Correlation Statistic for Dense Stereoscopic Matching},
 year =        {2005},
 pages =       {598--608},
 booktitle =   {SCIA '05: Proceedings of the 14th Scandinavian Conference on
                Image Analysis},
 publisher =   {Springer-Verlag},
 address =     {Heidelberg, Germany},
 isbn =        {0302-9743},
 volume   =    {3540},
 series =      {LNCS},
 number =      {3540},
 book_pages =  {1270},
 editor =      {Kalviainen, Heikki and Parkkinnen, Jussi and Kaarna, Arto},
 month =       {June},
 day =         {19-22},
 venue =       {Joensuu, Finland},
 annote = {A traditional solution of area-based stereo uses some kind
   of windowed pixel intensity correlation. This approach suffers from
   discretization artifacts which corrupt the correlation value. We
   introduce a new correlation statistic, which is completely
   invariant to image sampling, moreover it naturally provides a
   position of the correlation maximum between pixels. Hereby we can
   obtain sub-pixel disparity directly from sampling invariant and
   highly discriminable measurements without any postprocessing of the
   discrete disparity map. The key idea behind is to represent the
   image point neighbourhood in a different way, as a response to a
   bank of Gabor filters. The images are convolved with the filter
   bank and the complex correlation statistic (CCS) is evaluated from
   the responses without iterations. The magnitude of CCS measures the
   image similarity and the phase gives the sub-pixel position. Our
   experiments shows that CCS has even better sampling invariance and
   discriminability properties than the popular Birchfield-Tomasi
   dissimilarity, and the sub-pixel accuracy is higher than the
   Maximum Likelihood sub-pixel disparity window fitting disparity
   correction method we compared with. Results are shown on both
   synthetic and real data.},
 keywords =    {dense stereo matching, correlation statistic, 
                Gabor filter, image similarity, sub-pixel, 
                disparity, sampling invariance},
 prestige =    {international},
 authorship =  {50-50},
 project =     {1ET101210406},
 psurl       = {[PDF]