IS = { zkontrolovano 02 Jan 2007 },
  UPDATE  = { 2006-12-08 },
  author =      {Obdr{\v z}{\' a}lek, {\v S}t{\v e}p{\' a}n and
                 Matas, Ji{\v r}{\' \i}},
  title =       {Toward Category-Level Object Recognition},
  year =        {2006},
  pages =       {85-108},
  chapter =     {2},
  ch_title =    {Object Recognition using Local Affine Frames on Maximally Stable Extremal Regions},
  editor =      {Ponce, Jean and Hebert, Martial and Schmid, Cordelia
                 and  Zisserman, Andrew},
  publisher =   {Springer-Verlag},
  address =     {Berlin Heidelberg, Germany},
  isbn =        {3-540-68794-7},
  book_pages =  {618},
  authorship =  {50-50},
  annote =      {
   Methods based on distinguished regions (transformation covariant
   detectable regions) have achieved considerable success in object
   recognition, retrieval and matching problems in both still images and
   videos. The chapter focuses on a method exploiting local coordinate
   systems (local affine frames) established on maximally stable
   extremal regions. We provide a taxonomy of affine-covariant
   constructions of local coordinate systems, prove their affine
   covariance and present algorithmic details on their computation.

   Exploiting processes proposed for computation of affine-invariant
   local frames of reference, tentative region-to-region correspondences
   are established. Object recognition is formulated as a problem of
   finding a maximal set of geometrically consistent matches.

   State of the art results are reported on standard, publicly
   available, object recognition tests (COIL-100, ZuBuD, FOCUS). Change
   of scale, illumination conditions, out-of-plane rotation, occlusion ,
   locally anisotropic scale change and 3D translation of the viewpoint
   are all present in the test problems. },
  keywords =  {LAF, object recognition, affine invariance, MSER},
  project  =  {IST-004176 COSPAL, 1M0567},
  psurl    =  {[pdf]},