Elastic Alignment of Triangular Surface Meshes (bibtex)
by Zsolt Santa, Zoltan Kato
Abstract:
A novel region-based 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 simply found by solving a system of integral equations. Each equation is generated by integrating a non-linear function over the object domains. We derive recursive formulas for the efficient computation of these integrals for open and closed surface meshes. 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, brain surfaces and 3D human faces.
Reference:
Zsolt Santa, Zoltan Kato, Elastic Alignment of Triangular Surface Meshes, In International Journal of Computer Vision, volume 126, no. 11, pp. 1220-1244, 2018.
Bibtex Entry:
@string{ijcv="International Journal of Computer Vision"}
@Article{Santa-Kato2018,
  author =	 {Zsolt Santa and Zoltan Kato},
  title =	 {Elastic Alignment of Triangular Surface Meshes},
  journal =	 ijcv,
  year =	 2018,
  volume =	 126,
  number =	 11,
  pages =	 {1220-1244},
  month =	 nov,
  doi      = {10.1007/s11263-018-1084-4},
  abstract =	 {A novel region-based 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 simply found by solving a system
                  of integral equations. Each equation is generated by
                  integrating a non-linear function over the object
                  domains. We derive recursive formulas for the
                  efficient computation of these integrals for open
                  and closed surface meshes. 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, brain surfaces and 3D human faces.}
}
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