Efficient Globally Optimal 2D-to-3D Deformable Shape Matching

Zorah Lahner, Emanuele Rodola, Frank R. Schmidt, Michael M. Bronstein, Daniel Cremers

CVPR 2016

doi:10.1109/CVPR.2016.240 /cvpr/2016/lahner2016cvpr-efficient/

Abstract

We propose the first algorithm for non-rigid 2D-to-3D shape matching, where the input is a 2D query shape as well as a 3D target shape and the output is a continuous matching curve represented as a closed contour on the 3D shape. We cast the problem as finding the shortest circular path on the product 3-manifold of the two shapes. We prove that the optimal matching can be computed in polynomial time with a (worst-case) complexity of O(m*n^2*log(n)), where m and n denote the number of vertices on the 2D and the 3D shape respectively. Quantitative evaluation confirms that the method provides excellent results for sketch-based deformable 3D shape retrieval.

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Text

Lahner et al. "Efficient Globally Optimal 2D-to-3D Deformable Shape Matching." Conference on Computer Vision and Pattern Recognition, 2016. doi:10.1109/CVPR.2016.240

Markdown

[Lahner et al. "Efficient Globally Optimal 2D-to-3D Deformable Shape Matching." Conference on Computer Vision and Pattern Recognition, 2016.](https://mlanthology.org/cvpr/2016/lahner2016cvpr-efficient/) doi:10.1109/CVPR.2016.240

BibTeX

@inproceedings{lahner2016cvpr-efficient,
  title     = {{Efficient Globally Optimal 2D-to-3D Deformable Shape Matching}},
  author    = {Lahner, Zorah and Rodola, Emanuele and Schmidt, Frank R. and Bronstein, Michael M. and Cremers, Daniel},
  booktitle = {Conference on Computer Vision and Pattern Recognition},
  year      = {2016},
  doi       = {10.1109/CVPR.2016.240},
  url       = {https://mlanthology.org/cvpr/2016/lahner2016cvpr-efficient/}
}