Intrinsic Shape Matching by Planned Landmark Sampling
Abstract
Recently, the problem of intrinsic shape matching has received a lot of attention. A number of algorithms have been proposed, among which random‐sampling‐based techniques have been particularly successful due to their generality and efficiency. We introduce a new sampling‐based shape matching algorithm that uses a planning step to find optimized “landmark” points. These points are matched first in order to maximize the information gained and thus minimize the sampling costs. Our approach makes three main contributions: First, the new technique leads to a significant improvement in performance, which we demonstrate on a number of benchmark scenarios. Second, our technique does not require any keypoint detection. This is often a significant limitation for models that do not show sufficient surface features. Third, we examine the actual numerical degrees of freedom of the matching problem for a given piece of geometry. In contrast to previous results, our estimates take into account unprecise geodesics and potentially numerically unfavorable geometry of general topology, giving a more realistic complexity estimate.
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[98] answers how many correspondences are required to constrain deformations of non-rigid shapes.
“[98] further answers how many correspondences are required to constrain deformations of non-rigid shapes.”
From Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid (2013) · cites this paper as [98]
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Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid
Tam, G. K. L., Cheng, Z.-Q., Lai, Y.-K., Langbein, F. C., Liu, Y., Marshall, D., Martin, R. R., Sun, X.-F., & Rosin, P. L. (2013) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2012.310 · Cited by 679 · see citing works
- Authors
- Tevs, A., Berner, A., Wand, M., Ihrke, I., & Seidel, H. ‐.
- Affiliations
- Max Planck Institute for Informatics (DE)
- Venue
- Computer Graphics Forum
- Publisher
- Wiley
- Published
- 2011-04
- Volume
- 30
- Issue
- 2
- Pages
- 543-552
- ISSN
- 0167-7055 (ISSN-L)
- 1467-8659
- OpenAlex
- W2012385660
- Cited by
- 64
- References
- 30
- Citations by year
- 2024: 1 · 2023: 3 · 2022: 1 · 2021: 4 · 2020: 3 · 2019: 3 · 2018: 3 · 2017: 4 · 2016: 7 · 2015: 5 · 2014: 10 · 2013: 10 · 2012: 8
- FWCI
- 9.34
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computer Graphics Forum (publishedVersion)
- Max Planck Institute for Plasma Physics (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Computational Mechanics › 3D Shape Modeling and Analysis
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Computational Geometry and Mesh Generation
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Computer Graphics and Visualization Techniques
- Keywords
- degrees of freedom estimation, geodesics, random sampling
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