The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
Robust single-view geometry and motion reconstruction
Abstract
We present a framework and algorithms for robust geometry and motion reconstruction of complex deforming shapes. Our method makes use of a smooth template that provides a crude approximation of the scanned object and serves as a geometric and topological prior for reconstruction. Large-scale motion of the acquired object is recovered using a novel space-time adaptive, non-rigid registration method. Fine-scale details such as wrinkles and folds are synthesized with an efficient linear mesh deformation algorithm. Subsequent spatial and temporal filtering of detail coefficients allows transfer of persistent geometric detail to regions not observed by the scanner. We show how this two-scale process allows faithful recovery of small-scale shape and motion features leading to a high-quality reconstruction. We illustrate the robustness and generality of our algorithm on a variety of examples composed of different materials and exhibiting a large range of dynamic deformations.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“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 [32]
In the citing paper
“Yet, given only two surfaces and a high-dimensional deformation model (like [6], [32]), the solution can only be regularized by other prior knowledge-mostly in the form of regularizations to ensure smoothness.”
From Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid (2013) · cites this paper as [32]
In the citing paper
“Further challenges lie in (i) avoiding the need for markers or templates, and (ii) capturing and processing fine scale details [32].”
From Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid (2013) · cites this paper as [32]
Citations
Cites
2009 IEEE Conference on Computer Vision and Pattern Recognition
(2009) · doi:10.1109/cvpr14067.2009 · Cited by 5,646
A morphable model for the synthesis of 3D faces
Blanz, V., & Vetter, T. R. (1999) · ACM SIGGRAPH Conference (SIGGRAPH) · doi:10.1145/311535.311556 · Cited by 4,695
2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
(2015) · doi:10.1109/cvpr31182.2015 · Cited by 3,826
Control Chart Tests Based on Geometric Moving Averages
Roberts, S. W. (1959) · Technometrics · doi:10.1080/00401706.1959.10489860 · Cited by 1,526
Control Chart Tests Based on Geometric Moving Averages
Roberts, S. W. (2000) · Technometrics · doi:10.2307/1271439 · Cited by 1,260
Computing geodesic paths on manifolds
Kimmel, R., & Sethian, J. A. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.15.8431 · Cited by 1,067
The space of human body shapes: reconstruction and parameterization from range scans
Allen, B., Curless, B., & Popović, Z. (2003) · ACM SIGGRAPH 2003 Papers · doi:10.1145/1201775.882311 · Cited by 913
Optimal Step Nonrigid ICP Algorithms for Surface Registration
Amberg, B., Romdhani, S., & Vetter, T. R. (2007) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2007.383165 · Cited by 779
The space of human body shapes
Allen, B., Curless, B., & Popović, Z. (2003) · ACM Transactions on Graphics · doi:10.1145/882262.882311 · Cited by 725
Articulated mesh animation from multi-view silhouettes
Vlasic, D., Baran, I., Matusik, W., & Popović, J. (2008) · ACM Transactions on Graphics · doi:10.1145/1360612.1360696 · Cited by 618
Cited by
Sorted by citations
DynamicFusion: Reconstruction and tracking of non-rigid scenes in real-time
Newcombe, R. A., Fox, D., & Seitz, S. M. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298631 · Cited by 951
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
FAUST: Dataset and Evaluation for 3D Mesh Registration
Bogo, F., Romero, J., Loper, M., & Black, M. J. (2014) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2014.491 · Cited by 688
A Survey on Shape Correspondence
van Kaick, O. M., Zhang, H., Hamarneh, G., & Cohen‐Or, D. (2011) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2011.01884.x · Cited by 606
High-quality streamable free-viewpoint video
Collet, A., Chuang, M., Sweeney, P., Gillett, D., Evseev, D., Calabrese, D., Hoppe, H., Kirk, A. G., & Sullivan, S. (2015) · ACM Transactions on Graphics · doi:10.1145/2766945 · Cited by 577
Metadata
- Authors
- Li, H., Adams, B., Guibas, L. J., & Pauly, M.
- Affiliations
- ETH Zurich (CH)
- KU Leuven (BE)
- Stanford University (US)
- Venue
- ACM Transactions on Graphics
- Published
- 2009-12
- Volume
- 28
- Issue
- 5
- Pages
- 1-10
- ISSN
- 0730-0301 (ISSN-L)
- 1557-7368
- OpenAlex
- W1985290145
- Cited by
- 334
- References
- 44
- Citations by year
- 2026: 7 · 2025: 5 · 2024: 6 · 2023: 12 · 2022: 12 · 2021: 29 · 2020: 22 · 2019: 24 · 2018: 32 · 2017: 23 · 2016: 24 · 2015: 28 · 2014: 30 · 2013: 22 · 2012: 24
- FWCI
- 19.55
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- ACM Transactions on Graphics (publishedVersion)
- Funders
- National Science Foundation (ITR 0205671FRG 0354543FODAVA 808515)
- National Institutes of Health (GM-072970)
- Stavros Niarchos Foundation (200021-112122)
- Topics
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › 3D Shape Modeling and Analysis
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Computer Graphics and Visualization Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Keywords
- single-view reconstruction, 3D shape reconstruction, motion reconstruction, non-rigid registration, mesh deformation, temporal filtering, dynamic deformation
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 ›
Are you an author, or do you see a problem with this page? Request a review
