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Geodesics in shape space via variational time discretization

Publication ,  Journal Article
Wirth, B; Bar, L; Rumpf, M; Sapiro, G
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
November 6, 2009

A variational approach to defining geodesics in the space of implicitly described shapes is introduced in this paper. The proposed framework is based on the time discretization of a geodesic path as a sequence of pairwise matching problems, which is strictly invariant with respect to rigid body motions and ensures a 1-1 property of the induced flow in shape space. For decreasing time step size, the proposed model leads to the minimization of the actual geodesic length, where the Hessian of the pairwise matching energy reflects the chosen Riemannian metric on the shape space. Considering shapes as boundary contours, the proposed shape metric is identical to a physical dissipation in a viscous fluid model of optimal transportation. If the pairwise shape correspondence is replaced by the volume of the shape mismatch as a penalty functional, for decreasing time step size one obtains an additional optical flow term controlling the transport of the shape by the underlying motion field. The implementation of the proposed approach is based on a level set representation of shapes, which allows topological transitions along the geodesic path. For the spatial discretization a finite element approximation is employed both for the pairwise deformations and for the level set representation. The numerical relaxation of the energy is performed via an efficient multi-scale procedure in space and time. Examples for 2D and 3D shapes underline the effectiveness and robustness of the proposed approach. © 2009 Springer.

Duke Scholars

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

November 6, 2009

Volume

5681 LNCS

Start / End Page

288 / 302

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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Wirth, B., Bar, L., Rumpf, M., & Sapiro, G. (2009). Geodesics in shape space via variational time discretization. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5681 LNCS, 288–302. https://doi.org/10.1007/978-3-642-03641-5_22
Wirth, B., L. Bar, M. Rumpf, and G. Sapiro. “Geodesics in shape space via variational time discretization.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 5681 LNCS (November 6, 2009): 288–302. https://doi.org/10.1007/978-3-642-03641-5_22.
Wirth B, Bar L, Rumpf M, Sapiro G. Geodesics in shape space via variational time discretization. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2009 Nov 6;5681 LNCS:288–302.
Wirth, B., et al. “Geodesics in shape space via variational time discretization.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5681 LNCS, Nov. 2009, pp. 288–302. Scopus, doi:10.1007/978-3-642-03641-5_22.
Wirth B, Bar L, Rumpf M, Sapiro G. Geodesics in shape space via variational time discretization. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2009 Nov 6;5681 LNCS:288–302.

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

November 6, 2009

Volume

5681 LNCS

Start / End Page

288 / 302

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences