Non‐Rigid Registration Under Isometric Deformations
Open accessAbstract
We present a robust and efficient algorithm for the pairwise non‐rigid registration of partially overlapping 3D surfaces. Our approach treats non‐rigid registration as an optimization problem and solves it by alternating between correspondence and deformation optimization. Assuming approximately isometric deformations, robust correspondences are generated using a pruning mechanism based on geodesic consistency. We iteratively learn an appropriate deformation discretization from the current set of correspondences and use it to update the correspondences in the next iteration. Our algorithm is able to register partially similar point clouds that undergo large deformations, in just a few seconds. We demonstrate the potential of our algorithm in various applications such as example based articulated segmentation, and shape interpolation.
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To alleviate overfitting, [2], [6], [32] reduce the DoF explicitly by computing local transformations with respect to clusters or nodes, and most non-rigid registration methods use regularization to further constrain the solutions.
“To alleviate it, [2], [6], [32] reduce the DoF explicitly by computing local transformations with respect to clusters or nodes, and most non-rigid registration methods use regularization to further constrain the solutions.”
From Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid (2013) · cites this paper as [2]
Some constraints have been adopted by non-rigid registration; for example, an isometry constraint based on Euclidean distance in [46] is replaced by geodesic distance in [2].
“Some constraints have been adopted by non-rigid registration, e.g., [46] defines an isometry constraint based on Euclidean distance, which is replaced by geodesic distance in [2].”
From Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid (2013) · cites this paper as [2]
Many challenges posed by rigid registration have been addressed [2].
“Many challenges posed by rigid registration have been addressed [2].”
From Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid (2013) · cites this paper as [2]
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- Authors
- Huang, Q., Adams, B., Wicke, M., & Guibas, L. J.
- Affiliations
- Stanford University (US)
- Max Planck Center for Visual Computing and Communication (DE)
- ORCID
- Guibas, Leonidas J.
- Venue
- Computer Graphics Forum
- Publisher
- Wiley
- Published
- 2008-07
- Volume
- 27
- Issue
- 5
- Pages
- 1449-1457
- ISSN
- 0167-7055 (ISSN-L)
- 1467-8659
- OpenAlex
- W2123487031
- Cited by
- 279
- References
- 48
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 13 · 2023: 10 · 2022: 12 · 2021: 15 · 2020: 9 · 2019: 14 · 2018: 15 · 2017: 20 · 2016: 26 · 2015: 14 · 2014: 26 · 2013: 24 · 2012: 20
- FWCI
- 16.07
- Type
- journal article
- Language
- en
- Open access
- green
- lirias.kuleuven.be
- Licence
- Locations
- Computer Graphics Forum (publishedVersion)
- Lirias (KU Leuven) (submittedVersion, other-oa)
- Funders
- National Science Foundation (0354543, 0205671)
- University of Washington
- Vlaamse regering
- National Institutes of Health
- Defense Advanced Research Projects Agency (HR0011, HR0011-05-1-0007)
- Topics
- Physical Sciences › Engineering › Computational Mechanics › 3D Shape Modeling and Analysis
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Computer Graphics and Visualization Techniques
- Keywords
- non-rigid registration, isometric deformations, 3D surface registration, point clouds, alternating optimization, shape interpolation
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