Recovering Planar Homographies between 2D Shapes (bibtex)
by Jozsef Nemeth, Csaba Domokos, Zoltan Kato
Abstract:
Images taken from different views of a planar object are related by planar homography. Recovering the parameters of such transformations is a fundamental problem in computer vision with various applications. This paper proposes a novel method to estimate the parameters of a homography that aligns two binary images. It is obtained by solving a system of nonlinear equations generated by integrating linearly independent functions over the domains determined by the shapes. The advantage of the proposed solution is that it is easy to implement, less sensitive to the strength of the deformation, works without established correspondences and robust against segmentation errors. The method has been tested on synthetic as well as on real images and its efficiency has been demonstrated in the context of two different applications: alignment of hip prosthesis X-ray images and matching of traffic signs.
Reference:
Jozsef Nemeth, Csaba Domokos, Zoltan Kato, Recovering Planar Homographies between 2D Shapes, In Proceedings of International Conference on Computer Vision, Kyoto, Japan, pp. 2170-2176, 2009, IEEE.
Bibtex Entry:
@string{iccv="Proceedings of International Conference on Computer Vision"}
@InProceedings{Nemeth-etal2009a,
  author =	 {Nemeth, Jozsef and Domokos, {Cs}aba and Kato,
                  Zoltan},
  title =	 {Recovering Planar Homographies between {2D} Shapes},
  booktitle =	 iccv,
  pages =	 {2170--2176},
  year =	 2009,
  address =	 {Kyoto, Japan},
  month =	 sep,
  organization = {IEEE},
  publisher =	 {IEEE},
  abstract =	 {Images taken from different views of a planar object
                  are related by planar homography. Recovering the
                  parameters of such transformations is a fundamental
                  problem in computer vision with various
                  applications. This paper proposes a novel method to
                  estimate the parameters of a homography that aligns
                  two binary images. It is obtained by solving a
                  system of nonlinear equations generated by
                  integrating linearly independent functions over the
                  domains determined by the shapes. The advantage of
                  the proposed solution is that it is easy to
                  implement, less sensitive to the strength of the
                  deformation, works without established
                  correspondences and robust against segmentation
                  errors. The method has been tested on synthetic as
                  well as on real images and its efficiency has been
                  demonstrated in the context of two different
                  applications: alignment of hip prosthesis X-ray
                  images and matching of traffic signs.},
  pdf =          {http://www.sciweavers.org/external_ieee.php?u=http://www.stud.u-szeged.hu/Nemeth.Jozsef/iccv2009_cameraready.pdf},
}
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