@string{dicta="Proceedings of International Conference on Digital Image Computing: Techniques and Applications"}
@INPROCEEDINGS{Tanacs-etal2014b,
  author =	 {Attila Tan\'{a}cs and Andr\'as Majdik and J\'ozsef
                  Moln\'ar and Atul Rai and Zoltan Kato},
  title =	 {Establishing Correspondences between Planar Image
                  Patches},
  booktitle =	 dicta,
  year =	 2014,
  address =	 {Wollongong, New South Wales, Australia},
  month =	 nov,
  pages =	 {1-7},
  publisher =	 {IEEE},
  note =	 {Best Paper Award},
  abstract =	 {Finding correspondences between image pairs is a
                  fundamental task in computer vision. Herein, we
                  focus on establishing matches between images of
                  urban scenes which are typically composed of planar
                  surface patches with highly repetitive
                  structures. The latter property makes traditional
                  point-based methods unreliable. The basic idea of
                  our approach is to formulate the correspondence
                  problem in terms of homography estimation between
                  planar image regions: given a planar region in one
                  image, we are simultaneously looking for its
                  corresponding segmentation in the other image and
                  the planar homography acting between the two
                  regions. We will show, that due to the overlapping
                  views the general 8 degree of freedom (DOF) of the
                  homography mapping can be geometrically constrained
                  to 3 DOF and the resulting segmentation/registration
                  problem can be efficiently solved by finding the
                  region's occurrence in the second image using
                  pyramid representation and normalized mutual
                  information as the intensity similarity measure. The
                  method has been validated on a large database of
                  building images taken by different mobile cameras
                  and quantitative evaluation confirms robustness
                  against intensity variations, occlusions or the
                  presence of non-planar parts.  We also show examples
                  of 3D planar surface reconstruction as well as 2D
                  mosaicking.}
}