English

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

Computer Vision and Pattern Recognition 2022-01-24 v3

Abstract

We propose the first algorithm for non-rigid 2D-to-3D shape matching, where the input is a 2D shape represented as a planar curve and a 3D shape represented as a surface; the output is a continuous curve on the surface. We cast the problem as finding the shortest circular path on the product 3-manifold of the surface and the curve. We prove that the optimal matching can be computed in polynomial time with a (worst-case) complexity of O(mn2log(n))O(mn^2\log(n)), where mm and nn denote the number of vertices on the template curve and the 3D shape respectively. We also demonstrate that in practice the runtime is essentially linear in m ⁣ ⁣nm\!\cdot\! n making it an efficient method for shape analysis and shape retrieval. Quantitative evaluation confirms that the method provides excellent results for sketch-based deformable 3D shape retrieval.

Keywords

Cite

@article{arxiv.1601.06070,
  title  = {Efficient Globally Optimal 2D-to-3D Deformable Shape Matching},
  author = {Zorah Lähner and Emanuele Rodolà and Frank R. Schmidt and Michael M. Bronstein and Daniel Cremers},
  journal= {arXiv preprint arXiv:1601.06070},
  year   = {2022}
}

Comments

Extended chapter of conference paper in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2016 to be published in Shape Analysis: Euclidean, Discrete and Algebraic Geometric Methods by Springer

R2 v1 2026-06-22T12:35:00.348Z