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A Gromov-Hausdorff Framework with Diffusion Geometry for Topologically-Robust Non-rigid Shape Matching
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“In cases with large topological changes, the isometry assumption may fail [38]; handling such issues is a challenging task.”
From Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid (2013) · cites this paper as [38]
In the citing paper
“Recent intrinsic techniques [36], [38], [39] use low dimensional embedding to by-pass the high-dimensionality problem by assuming a strong inelastic isometry constraint.”
From Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid (2013) · cites this paper as [38]
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Cites
A Method for Registration of 3-D Shapes
Besl, P., & Mckay, N. D. (1992) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.121791 · Cited by 22,163
A Global Geometric Framework for Nonlinear Dimensionality Reduction
Tenenbaum, J. B., Silva, V. D., & Langford, J. C. (2000) · Science · doi:10.1126/science.290.5500.2319 · Cited by 13,585
Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
Belkin, M., & Niyogi, P. (2003) · Neural Computation · doi:10.1162/089976603321780317 · Cited by 7,562
Chung, F. (1996) · Regional conference series in mathematics · doi:10.1090/cbms/092 · Cited by 5,918
Burago, D., Burago, Y., & Ivanov, S. (2001) · Graduate Studies in Mathematics · doi:10.1090/gsm/033 · Cited by 2,598
Eisenhart, L. P. (1950) · Princeton University Press eBooks · doi:10.1515/9781400884216 · Cited by 2,543
Coifman, R. R., & Lafon, S. (2006) · Applied and Computational Harmonic Analysis · doi:10.1016/j.acha.2006.04.006 · Cited by 2,380
Discrete Differential-Geometry Operators for Triangulated 2-Manifolds
Meyer, M., Desbrun, M., Schröder, P., & Barr, A. H. (2003) · Mathematics and visualization · doi:10.1007/978-3-662-05105-4_2 · Cited by 1,910
Osada, R., Funkhouser, T. A., Chazelle, B., & Dobkin, D. (2002) · ACM Transactions on Graphics · doi:10.1145/571647.571648 · Cited by 1,688
Coifman, R. R., Lafon, S., Lee, A. B., Maggioni, M., Nadler, B., Warner, F., & Zucker, S. W. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0500334102 · Cited by 1,675
Research works printed but not linked: 3
- Bronstein, A. M., Bronstein, M. M., & Kimmel, R. (2008). Numerical geometry of nonrigid shapes. Berlin: Springer.
- Lafon, S. (2004). Diffusion maps and geometric harmonics. Ph.D. dissertation, Yale University.
- Mémoli, F., Sapiro, G., & Thompson, P. (2006). Geometric surface and brain warping via geodesic minimizing Lipschitz extensions. In MFCA-2006 international workshop on mathematical foundations of computational anatomy, Copenhagen.
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(2012) · SpringerReference · doi:10.1007/springerreference_186913 · Cited by 3
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Self-citation
Metadata
- Authors
- Bronstein, A. M., Bronstein, M. M., Kimmel, R., Mahmoudi, M., & Sapiro, G.
- Affiliations
- Technion – Israel Institute of Technology (IL)
- University of Minnesota (US)
- Corresponding author
- Sapiro, Guillermo
- Venue
- International Journal of Computer Vision
- Published
- 2009-10-08
- Volume
- 89
- Issue
- 2-3
- Pages
- 266-286
- ISSN
- 0920-5691 (ISSN-L)
- 1573-1405
- OpenAlex
- W1982465050
- Cited by
- 267
- References
- 78
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 6 · 2023: 4 · 2022: 5 · 2021: 10 · 2020: 12 · 2019: 16 · 2018: 19 · 2017: 22 · 2016: 17 · 2015: 18 · 2014: 27 · 2013: 30 · 2012: 31
- FWCI
- 25.28
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- www.springer.com/tdm (tdm)
- Locations
- International Journal of Computer Vision (publishedVersion)
- University of Minnesota Digital Conservancy (University of Minnesota) (submittedVersion)
- Funders
- National Institutes of Health
- Defense Advanced Research Projects Agency
- Topics
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › 3D Shape Modeling and Analysis
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Topological and Geometric Data Analysis
- Physical Sciences › Mathematics › Applied Mathematics › Geometric Analysis and Curvature Flows
- Keywords
- non-rigid shape matching, shape recognition, diffusion distance, Gromov-Hausdorff distance, metric geometry, topological robustness, geodesic distance, non-rigid deformation, missing data
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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