Correspondence-Less Non-Rigid Registration of Triangular Surface Meshes (bibtex)
by Zsolt Santa, Zoltan Kato
Abstract:
A novel correspondence-less approach is proposed to find a thin plate spline map between a pair of deformable 3D objects represented by triangular surface meshes. The proposed method works without landmark extraction and feature correspondences. The aligning transformation is found simply by solving a system of nonlinear equations. Each equation is generated by integrating a nonlinear function over the object’s domains. We derive recursive formulas for the efficient computation of these integrals. Based on a series of comparative tests on a large synthetic dataset, our triangular mesh-based algorithm outperforms state of the art methods both in terms of computing time and accuracy. The applicability of the proposed approach has been demonstrated on the registration of 3D lung CT volumes.
Reference:
Zsolt Santa, Zoltan Kato, Correspondence-Less Non-Rigid Registration of Triangular Surface Meshes, In Proceedings of International Conference on Computer Vision and Pattern Recognition, Portland, Oregon, USA, pp. 2275-2282, 2013, IEEE.
Bibtex Entry:
@string{cvpr="Proceedings of International Conference on Computer Vision and Pattern Recognition"}
@INPROCEEDINGS{Santa-Kato2013,
  author = {Zsolt Santa and Zoltan Kato},
  title = {Correspondence-Less Non-Rigid Registration of Triangular Surface
	Meshes},
  booktitle = cvpr,
  year = {2013},
  pages = {2275--2282},
  address = {Portland, Oregon, USA},
  month = jun,
  organization = {IEEE},
  publisher = {IEEE},
  doi = {10.1109/CVPR.2013.295},
  abstract = {A novel correspondence-less approach is proposed to find a thin plate
	spline map between a pair of deformable 3D objects represented by
	triangular surface meshes. The proposed method works without landmark
	extraction and feature correspondences. The aligning transformation
	is found simply by solving a system of nonlinear equations. Each
	equation is generated by integrating a nonlinear function over the
	object’s domains. We derive recursive formulas for the efficient
	computation of these integrals. Based on a series of comparative
	tests on a large synthetic dataset, our triangular mesh-based algorithm
	outperforms state of the art methods both in terms of computing time
	and accuracy. The applicability of the proposed approach has been
	demonstrated on the registration of 3D lung CT volumes.}
}
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