@InProceedings{Srajer3DV2014,
  IS = { zkontrolovano 03 Jan 2015 },
  UPDATE  = { 2014-12-19 },
  author =      {{\v S}rajer, Filip and Schwing, Alexander~G. and
                  Pollefeys, Marc and Pajdla, Tom{\' a}{\v s} },
  affiliation = {13133-NULL-NULL-13133},
  title =       {{MatchBox: Indoor Image Matching via Box-like Scene Estimation}},
  year =        {2014},
  pages =       {705-712},
  booktitle =   {3DV 2014: International Conference on 3D Vision},
  editor =      {Lisa O'Conner},
  publisher =   {IEEE Computer Society Press},
  address =     {Los Alamitos, USA},
  isbn =        {978-1-4799-7000-1},
  book_pages =  {730},
  month =       {December},
  day =         {8-11},
  venue =       {Tokyo, Japan},
  annote =      {Keypoint matching in images of indoor scenes
                  traditionally employs features like SIFT, GIST and
                  HOG. While features work very well for two images
                  related to each other by small camera
                  transformations, we commonly observe a drop in
                  performance for patches representing scene elements
                  visualized from a very different perspective. Since
                  increasing the space of considered local
                  transformations for feature matching decreases their
                  discriminative abilities, we propose a more global
                  approach inspired by the recent success of monocular
                  scene understanding. In particular we propose to
                  reconstruct a box-like model of the scene from every
                  single image and use it to rectify images before
                  matching. We show that a monocular scene model
                  reconstruction and rectification preceding standard
                  feature matching significantly improves keypoint
                  matching and dramatic ally improves reconstruction
                  of difficult indoor scenes.},
  keywords =    {image matching, indoor, scene layout},
  prestige =    {international},
  project =     {TACR TA02011275 ATOM, SGS12/191/OHK3/3T/13},
  doi =         {},
}