The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
Möbius voting for surface correspondence
Abstract
The goal of our work is to develop an efficient, automatic algorithm for discovering point correspondences between surfaces that are approximately and/or partially isometric. Our approach is based on three observations. First, isometries are a subset of the Möbius group, which has low-dimensionality -- six degrees of freedom for topological spheres, and three for topological discs. Second, computing the Möbius transformation that interpolates any three points can be computed in closed-form after a mid-edge flattening to the complex plane. Third, deviations from isometry can be modeled by a transportation-type distance between corresponding points in that plane. Motivated by these observations, we have developed a Möbius Voting algorithm that iteratively: 1) samples a triplet of three random points from each of two point sets, 2) uses the Möbius transformations defined by those triplets to map both point sets into a canonical coordinate frame on the complex plane, and 3) produces "votes" for predicted correspondences between the mutually closest points with magnitude representing their estimated deviation from isometry. The result of this process is a fuzzy correspondence matrix, which is converted to a permutation matrix with simple matrix operations and output as a discrete set of point correspondences with confidence values. The main advantage of this algorithm is that it can find intrinsic point correspondences in cases of extreme deformation. During experiments with a variety of data sets, we find that it is able to find dozens of point correspondences between different object types in different poses fully automatically.
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
“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 [39]
In the citing paper
“These transformations are similar to the domain theory in analytical learning-a global rule, one reason why these techniques can be cast as optimization problems and solved using the Hough transform [17], [39] or RANSAC technique [4], [71] efficiently.”
From Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid (2013) · cites this paper as [39]
Citations
Cites
Distinctive Image Features from Scale-Invariant Keypoints
Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589
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
The Earth Mover's Distance as a Metric for Image Retrieval
Rubner, Y., Tomasi, C., & Guibas, L. (2000) · International Journal of Computer Vision · doi:10.1023/a:1026543900054 · Cited by 5,547
Generalizing the Hough transform to detect arbitrary shapes
Ballard, D. H. (1981) · Pattern Recognition · doi:10.1016/0031-3203(81)90009-1 · Cited by 4,434
Efficient variants of the ICP algorithm
Rusinkiewicz, S., & Levoy, M. (2002) · Proceedings Third International Conference on 3-D Digital Imaging and Modeling · doi:10.1109/im.2001.924423 · Cited by 3,945
Using spin images for efficient object recognition in cluttered 3D scenes
Johnson, A., & Hebert, M. (1999) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.765655 · Cited by 2,656
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
A new point matching algorithm for non-rigid registration
Chui, H., & Rangarajan, A. (2003) · Computer Vision and Image Understanding · doi:10.1016/s1077-3142(03)00009-2 · Cited by 1,560
SCAPE: shape completion and animation of people
Anguelov, D., Srinivasan, P., Koller, D., Thrun, S., Rodgers, J., & Davis, J. (2005) · ACM Transactions on Graphics · doi:10.1145/1073204.1073207 · Cited by 1,489
Computing Discrete Minimal Surfaces and Their Conjugates
Pinkall, U., & Polthier, K. (1993) · Experimental Mathematics · doi:10.1080/10586458.1993.10504266 · Cited by 1,278
Flagged first, then by citations
Research works printed but not linked: 1
- 10.5555/1731309.1731327 · DOI
Cited by
Sorted by citations
Items 101–200 of 332
Shape matching based on diffusion embedding and on mutual isometric consistency
Sharma, A. K., & Horaud, R. (2010) · 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops · doi:10.1109/cvprw.2010.5543278 · Cited by 32
Complex Functional Maps: A Conformal Link Between Tangent Bundles
Donati, N., Corman, É., Melzi, S., & Ovsjanikov, M. (2022) · Computer Graphics Forum · doi:10.1111/cgf.14437 · Cited by 34
Srivastava, A., Turaga, P. K., & Kurtek, S. (2012) · Image and Vision Computing · doi:10.1016/j.imavis.2012.03.006 · Cited by 30
SuperMatching: Feature Matching Using Supersymmetric Geometric Constraints
Cheng, Z., Chen, Y., Martin, R. R., Lai, Y., & Wang, A. (2013) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2013.15 · Cited by 32
Dubrovina, A., & Kimmel, R. (2011) · Advances in Adaptive Data Analysis · doi:10.1142/s1793536911000829 · Cited by 32
Coherent Point Drift Revisited for Non-rigid Shape Matching and Registration
Fan, A., Ma, J., Tian, X. S., Mei, X., & Lin, W. S. (2022) · 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/cvpr52688.2022.00148 · Cited by 31
A Genetic Isometric Shape Correspondence Algorithm with Adaptive Sampling
Sahillioğlu, Y. (2018) · ACM Transactions on Graphics · doi:10.1145/3243593 · Cited by 29
Continuous Matching via Vector Field Flow
Corman, É., Ovsjanikov, M., & Chambolle, A. (2015) · Computer Graphics Forum · doi:10.1111/cgf.12702 · Cited by 27
Symmetry factored embedding and distance
Lipman, Y., Chen, X., Daubechies, I., & Funkhouser, T. A. (2010) · ACM SIGGRAPH Conference (SIGGRAPH) · doi:10.1145/1833349.1778840 · Cited by 27
Self-citationSurface Comparison with Mass TransportationPreprint
Lipman, Y., & Daubechies, I. C. (2009) · arXiv (Cornell University) · doi:10.48550/arxiv.0912.3488 · Cited by 27
Self-citationCreating and Animating Subject‐Specific Anatomical Models
Gilles, B., Revéret, L., & Pai, D. K. (2010) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2010.01718.x · Cited by 26
Transferring and fitting fixed-sized garments onto bodies of various dimensions and postures
Jiang, L., Ye, J., Sun, L., & Li, J. (2018) · Computer-Aided Design · doi:10.1016/j.cad.2018.08.002 · Cited by 26
Learned Binary Spectral Shape Descriptor for 3D Shape Correspondence
Xie, J., Wang, M., & Fang, Y. (2016) · 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.2016.360 · Cited by 25
Dirichlet Energy for Analysis and Synthesis of Soft Maps
Solomon, J., Guibas, L. J., & Butscher, A. (2013) · Computer Graphics Forum · doi:10.1111/cgf.12186 · Cited by 25
Partial 3‐D Correspondence from Shape Extremities
Sahillioğlu, Y., & Yemez, Y. (2014) · Computer Graphics Forum · doi:10.1111/cgf.12278 · Cited by 24
Robust Structure‐Based Shape Correspondence
Kleiman, Y., & Ovsjanikov, M. (2018) · Computer Graphics Forum · doi:10.1111/cgf.13389 · Cited by 25
Efficient Deformable Shape Correspondence via Kernel MatchingPreprint
Lähner, Z., Vestner, M., Boyarski, A., Litany, O., Slossberg, R., Remez, T., Rodolà, E., Bronstein, A. M., Bronstein, M. M., Kimmel, R., et al. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1707.08991 · Cited by 25
Deformable registration using patch-wise shape matching
Bonarrigo, F., Signoroni, A., & Botsch, M. (2014) · Graphical Models · doi:10.1016/j.gmod.2014.04.004 · Cited by 24
Baden, A., Crane, K., & Kazhdan, M. (2018) · Computer Graphics Forum · doi:10.1111/cgf.13503 · Cited by 24
Cho, Y., Seong, J., Shin, S. Y., Jeong, Y., Kim, J. H., Qiu, A., Im, K., Lee, J. M., & Na, D. L. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.05.066 · Cited by 24
3D human motion analysis framework for shape similarity and retrieval
Slama, R., Wannous, H., & Daoudi, M. (2014) · Image and Vision Computing · doi:10.1016/j.imavis.2013.12.011 · Cited by 24
Bending-Invariant Correspondence Matching on 3-D Human Bodies for Feature Point Extraction
Li, S., Wang, C. C. L., & Hui, K. (2011) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2011.2143404 · Cited by 24
Animation Setup Transfer for 3D Characters
Avril, Q., Ghafourzadeh, D., Ramachandran, S., Fallahdoust, S., Ribet, S., Dionne, O., de Lasa, M., & Paquette, E. (2016) · Computer Graphics Forum · doi:10.1111/cgf.12816 · Cited by 24
Stable Region Correspondences Between Non‐Isometric Shapes
Ganapathi‐Subramanian, V., Thibert, B., Ovsjanikov, M., & Guibas, L. (2016) · Computer Graphics Forum · doi:10.1111/cgf.12969 · Cited by 22
Analysis and Visualization of Maps Between Shapes
Ovsjanikov, M., Ben‐Chen, M., Chazal, F., & Guibas, L. J. (2013) · Computer Graphics Forum · doi:10.1111/cgf.12076 · Cited by 22
Fuzzy Geodesics and Consistent Sparse Correspondences For: eformable Shapes
Sun, J. Z., Chen, X., & Funkhouser, T. A. (2010) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2010.01762.x · Cited by 21
Self-citationPairwise Harmonics for Shape Analysis
Zheng, Y., Tai, C., Zhang, E., & Xu, P. (2012) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2012.309 · Cited by 21
Shape Analysis of Planar Multiply-Connected Objects Using Conformal Welding
Lui, L. M., Zeng, W., Yau, S., & Gu, X. D. (2014) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2013.215 · Cited by 21
Scale Normalization for Isometric Shape Matching
Sahillioğlu, Y., & Yemez, Y. (2012) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2012.03216.x · Cited by 20
Automatic Alignment of Genus-Zero Surfaces
Koehl, P., & Hass, J. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2013.139 · Cited by 20
Symmetry-Aware Nonrigid Matching of Incomplete 3D Surfaces
Yoshiyasu, Y., Yoshida, E., Yokoi, K., & Sagawa, R. (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.2014.534 · Cited by 20
Intrinsic dense 3D surface tracking
Zeng, Y., Wang, C., Wang, Y., Gu, X., Samaras, D., & Paragios, N. (2011) · CVPR 2011 · doi:10.1109/cvpr.2011.5995513 · Cited by 19
A Survey on Non-rigid 3D Shape Analysis
Laga, H. (2018) · arXiv.org · doi:10.1016/b978-0-12-811889-4.00007-5 · Cited by 26
Lai, R., & Hongkai Zhao, C. (2017) · SIAM Journal on Imaging Sciences · doi:10.1137/16m1068827 · Cited by 19
A Condition Number for Non‐Rigid Shape Matching
Ovsjanikov, M., Qi-xing Huang, A., & Guibas, L. J. (2011) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2011.02024.x · Cited by 18
Matching the LBO Eigenspace of Non-Rigid Shapes via High Order Statistics
Shtern, A., & Kimmel, R. (2014) · Axioms · doi:10.3390/axioms3030300 · Cited by 17
Predicting anatomical landmarks and bone morphology of the femur using local region matching
Phan, C.-B., & Koo, S. (2015) · International Journal of Computer Assisted Radiology and Surgery · doi:10.1007/s11548-015-1155-8 · Cited by 16
Iterative Closest Spectral Kernel Maps
Shtern, A., & Kimmel, R. (2014) · International Conference on 3D Vision (3DV) · doi:10.1109/3dv.2014.24 · Cited by 17
Spectral descriptors for deformable shapesPreprint
Bronstein, A. M. (2011) · arXiv (Cornell University) · doi:10.48550/arxiv.1110.5015 · Cited by 17
Compatible intrinsic triangulations
Takayama, K. (2022) · ACM Transactions on Graphics · doi:10.1145/3528223.3530175 · Cited by 16
A low-dimensional representation for robust partial isometric correspondences computation
Brunton, A., Wand, M., Wuhrer, S., Seidel, H., & Weinkauf, T. (2013) · Graphical Models · doi:10.1016/j.gmod.2013.11.003 · Cited by 16
Abiri, A., Ding, Y.-C., Abiri, P., Packard, R. R. S., Vedula, V., Marsden, A., Kuo, C.-C. J., & Tzung, H.-A. K. (2018) · Annals of Biomedical Engineering · doi:10.1007/s10439-018-02113-z · Cited by 15
Hierarchical Matching of Non-rigid Shapes
Raviv, D., Dubrovina, A., & Kimmel, R. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-24785-9_51 · Cited by 16
Multiple Shape Correspondence by Dynamic Programming
Sahillioğlu, Y., & Yemez, Y. (2014) · Computer Graphics Forum · doi:10.1111/cgf.12480 · Cited by 17
Near-Regular Structure Discovery Using Linear Programming
Huang, Q.-X., Guibas, L., & Mitra, N. (2014) · ACM Transactions on Graphics · doi:10.1145/2535596 · Cited by 16
Constructing common base domain by cues from Voronoi diagram
Kwok, T.-H., Zhang, Y., & Wang, C. C. L. (2012) · Graphical Models · doi:10.1016/j.gmod.2012.03.012 · Cited by 15
Mathematical Tools for Shape Analysis and Description
Biasotti, S., Falcidieno, B., Giorgi, D., & Spagnuolo, M. (2014) · Synthesis lectures on computer graphics and animation · doi:10.1007/978-3-031-79558-9 · Cited by 17
Vector Field Map Representation for Near Conformal Surface Correspondence
Wang, Y., Liu, B., Zhou, K., & Tong, Y. (2017) · Computer Graphics Forum · doi:10.1111/cgf.13312 · Cited by 15
A Low-dimensional Representation for Robust Partial Isometric Correspondences Computation
Brunton, A., Wand, M., Wuhrer, S., Seidel, H., & Weinkauf, T. (2014) · Max Planck Digital Library · Cited by 15
E3Sym: Leveraging E(3) Invariance for Unsupervised 3D Planar Reflective Symmetry Detection
Li, R.-W., Zhang, L., Li, C., Lai, Y., & Gao, L. (2023) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01337 · Cited by 14
Multilevel Optimization for Registration of Deformable Point Clouds
Chaudhury, A. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2020.3019649 · Cited by 14
Diffusion Geometry Derived Keypoints and Local Descriptors for 3D Deformable Shape Analysis
Wang, X., Bennamoun, M., Sohel, F. A., & Lei, H. (2020) · Journal of Circuits Systems and Computers · doi:10.1142/s021812662150016x · Cited by 13
Feature correspondences using Morse Smale complex
Feng, W., Huang, J., Ju, T., & Bao, H. (2012) · The Visual Computer · doi:10.1007/s00371-012-0674-3 · Cited by 13
Conformal Mapping with as Uniform as Possible Conformal Factor
Aflalo, Y., Kimmel, R., & Zibulevsky, M. (2013) · SIAM Journal on Imaging Sciences · doi:10.1137/110845860 · Cited by 13
Higher-Order Graph Principles towards Non-Rigid Surface Registration
Zeng, Y., Wang, C., Gu, X. D., Samaras, D., & Nikos Paragios, A. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2528240 · Cited by 13
Non-rigid Registration in 3D Implicit Vector Space
Cheng, Z., Jiang, W., Dang, G., Martin, R. R., Li, J., Li, H., Chen, Y., Wang, Y., Li, B., Xu, K., et al. (2010) · IEEE International Conference on Shape Modeling and Applications · doi:10.1109/smi.2010.21 · Cited by 13
Geometric-Feature-Based Spectral Graph Matching in Pharyngeal Surface Registration
Zhao, Q., Pizer, S. M., Niethammer, M., & Rosenman, J. G. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-10404-1_33 · Cited by 13
Boosting Local Shape Matching for Dense 3D Face Correspondence
Fan, Z., Hu, X.-Y., Chen, C., & Peng, S.-L. (2019) · Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2019.01120 · Cited by 20
Shape Analysis of Planar Objects with Arbitrary Topologies Using Conformal Geometry
Lui, L. M., Zeng, W., Yau, S., & Gu, X. D. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-15555-0_49 · Cited by 12
Smooth bijective maps between arbitrary planar polygons
Schneider, T., & Hormann, K. (2015) · Computer Aided Geometric Design · doi:10.1016/j.cagd.2015.03.010 · Cited by 12
Joint Map and Symmetry Synchronization
Sun, Y., Liang, Z., Huang, X., & Qi-xing Huang, A. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01228-1_16 · Cited by 12
Möbius transformation and coupled-wave theory: Complete identification of the transfer matrix
Koufidis, S. F., & McCall, M. W. (2022) · Physical Review A · doi:10.1103/physreva.106.062213 · Cited by 12
Intrinsic 3D Dynamic Surface Tracking based on Dynamic Ricci Flow and Teichmüller Map
Yu, X., Lei, N., Wang, Y., & Gu, X. D. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.576 · Cited by 12
Template-based surface reconstruction from cross-sections
Holloway, M., Grimm, C. M., & Ju, T. (2016) · Computers & Graphics · doi:10.1016/j.cag.2016.05.012 · Cited by 12
Detail-Preserving Mesh Unfolding for Nonrigid Shape Retrieval
Sahillioğlu, Y., & Kavan, L. (2016) · ACM Transactions on Graphics · doi:10.1145/2893477 · Cited by 12
Symmetry aware embedding for shape correspondence
Yoshiyasu, Y., Yoshida, E., & Guibas, L. J. (2016) · Computers & Graphics · doi:10.1016/j.cag.2016.07.002 · Cited by 12
Correspondence estimation for non-rigid point clouds with automatic part discovery
Guo, H., Zhu, D.-H., & Mordohai, P. (2016) · The Visual Computer · doi:10.1007/s00371-015-1136-5 · Cited by 12
Symmetry Robust Descriptor for Non‐Rigid Surface Matching
Zhang, Z., Yin, K., & Foong, K. W. C. (2013) · Computer Graphics Forum · doi:10.1111/cgf.12243 · Cited by 11
Zell, E., & Botsch, M. (2013) · doi:10.1145/2486042.2486045 · Cited by 11
Zeng, Y., Wang, C., Gu, X. D., Samaras, D., & Nikos Paragios, A. (2013) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2013.417 · Cited by 11
Mathematical Tools for Shape Analysis and Description
Biasotti, S., Falcidieno, B., Giorgi, D., & Spagnuolo, M. (2014) · Synthesis lectures on computer graphics and animation · doi:10.2200/s00588ed1v01y201407cgr016 · Cited by 10
Symmetric Volume Maps: Order-invariant Volumetric Mesh Correspondence with Free Boundary
Abulnaga, S. M., Stein, O., Golland, P., & Solomon, J. (2022) · ACM Transactions on Graphics · doi:10.1145/3572897 · Cited by 10
Properly constrained orthonormal functional maps for intrinsic symmetries
Liu, X., Li, S., Liu, R., Wang, J., Wang, H., & Cao, J. (2014) · Computers & Graphics · doi:10.1016/j.cag.2014.09.016 · Cited by 10
Efficient view-based 3d reflection symmetry detection
Li, B., Johan, H., Ye, Y., & Lu, Y. (2014) · doi:10.1145/2669043.2669045 · Cited by 10
Partial correspondence of 3D shapes using properties of the nearest-neighbor field
Arbel, N., Tal, A., & Zelnik‐Manor, L. (2019) · Computers & Graphics · doi:10.1016/j.cag.2019.05.011 · Cited by 10
Su, Y.-H., Huang, K., & Hannaford, B. (2019) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros40897.2019.8968489 · Cited by 10
Wu, Y., Yang, J., & Zhao, J.-L. (2020) · Computers & graphics · doi:10.1016/j.cag.2020.09.004 · Cited by 13
Image Matching Using Mutual k-Nearest Neighbor Graph
Li, T., Jiang, B., Tu, Z., Luo, B., & Tang, J. (2014) · Communications in computer and information science · doi:10.1007/978-3-662-46248-5_34 · Cited by 10
A shape deformation algorithm for constrained multidimensional scaling
Sahillioğlu, Y. (2015) · Computers & Graphics · doi:10.1016/j.cag.2015.10.003 · Cited by 10
Robust Dense Registration of Partial Nonrigid Shapes
Hou, T., & Qin, H. (2011) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2011.267 · Cited by 10
Tierny, J., Daniels, J., Nonato, L. G., Pascucci, V., & Silva, C. T. (2011) · Computer-Aided Design · doi:10.1016/j.cad.2011.08.020 · Cited by 10
Dense Point‐to‐Point Correspondences Between Genus‐Zero Shapes
Lee, S. C., & Kazhdan, M. (2019) · Computer graphics forum (Print) · doi:10.1111/cgf.13787 · Cited by 15
Seo, J., Seol, Y., Wi, D., Kim, Y., & Noh, J. (2010) · Computer Animation and Virtual Worlds · doi:10.1002/cav.358 · Cited by 10
Exploring partial intrinsic and extrinsic symmetry in 3D medical imaging
Fotouhi, J., Taylor, G., Unberath, M., Johnson, A. A., Lee, S. C., Osgood, G. M., Armand, M., & Navab, N. (2021) · Medical Image Analysis · doi:10.1016/j.media.2021.102127 · Cited by 9
μMatch: 3D Shape Correspondence for Biological Image Data
Klatzow, J., Dalmasso, G., Martínez‐Abadías, N., Sharpe, J. A., & Uhlmann, V. (2022) · Frontiers in Computer Science · doi:10.3389/fcomp.2022.777615 · Cited by 9
Non-rigid point set registration: recent trends and challenges
Yuan, X., & Maharjan, A. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-022-10292-4 · Cited by 11
3D Shape Registration Using Spectral Graph Embedding and Probabilistic Matching
Sharma, A. K., Horaud, R., & Mateus, D. (2017) · CRC Press eBooks · doi:10.1201/b12281-15 · Cited by 9
Hierarchical Framework for Shape Correspondence
Raviv, D., Dubrovina, A., & Kimmel, R. (2013) · Numerical Mathematics Theory Methods and Applications · doi:10.4208/nmtma.2013.mssvm13 · Cited by 9
Surface Registration in the Presence of Missing Patches and Topology Change.
Zhao, Q., Price, J., Pizer, S. M., Niethammer, M., Alterovitz, R., & Rosenman, J. G. (2015) · MIUA · Cited by 9
Automatic Schelling Point Detection From Meshes
Chen, G., Dai, H., Zhou, T., Shen, J., & Shao, L. (2022) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2022.3144143 · Cited by 10
The continuous Procrustes distance between two surfacesPreprint
Daubechies, Y. L. R. A.-A. I. (2011) · arXiv (Cornell University) · doi:10.48550/arxiv.1106.4588 · Cited by 9
Augmented Paths and Reodesics for Topologically-Stable Matching
Sahillioğlu, Y., & Horsman, D. (2022) · ACM Transactions on Graphics · doi:10.1145/3554978 · Cited by 8
Conformal Surface Alignment with Optimal Möbius Search
Le, H., Chin, T.-J., & Suter, D. (2016) · 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.2016.275 · Cited by 8
3D Shape Restoration via Matrix Recovery
Lu, M., Zheng, B., Takamatsu, J., Nishino, K., & Ikeuchi, K. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-22819-3_31 · Cited by 8
Semi‐isometric Registration of Line Features for Flexible Fitting of Protein Structures
Abeysinghe, S. S., Baker, M. L., Chiu, W., & Ju, T. (2010) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2010.01813.x · Cited by 8
A non-rigid 3D model retrieval method based on scale-invariant heat kernel signature features
Li, P., Ma, H., & Ming, A. (2016) · Multimedia Tools and Applications · doi:10.1007/s11042-016-3606-9 · Cited by 8
Linear variational principle for Riemann mappings and discrete conformality
Dym, N., Slutsky, R., & Lipman, Y. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1809731116 · Cited by 8
Self-citationConsistent Shape Matching via Coupled Optimization
Azencot, O., Dubrovina, A., & Guibas, L. J. (2019) · Computer Graphics Forum · doi:10.1111/cgf.13786 · Cited by 8
Approximate Greedy Clustering and Distance Selection for Graph Metrics
Eppstein, D., Har-Peled, S., & Sidiropoulos, A. (2015) · Journal of computational geometry · doi:10.20382/jocg.v11i1a25 · Cited by 8
4D Human Body Correspondences from Panoramic Depth Maps
Li, Z., Wu, M., Zhou, W., & Jingyi Yu, A. (2018) · 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.2018.00304 · Cited by 7
Metadata
- Authors
- Lipman, Y., & Funkhouser, T.
- Affiliations
- Princeton University (US)
- Venue
- ACM Transactions on Graphics
- Published
- 2009-07-27
- Volume
- 28
- Issue
- 3
- Pages
- 1-12
- ISSN
- 0730-0301 (ISSN-L)
- 1557-7368
- OpenAlex
- W2105106232
- Cited by
- 332
- References
- 49
- Citations by year
- 2026: 6 · 2025: 7 · 2024: 4 · 2023: 8 · 2022: 15 · 2021: 3 · 2020: 15 · 2019: 13 · 2018: 27 · 2017: 25 · 2016: 34 · 2015: 18 · 2014: 37 · 2013: 38 · 2012: 30
- FWCI
- 27.26
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- ACM Transactions on Graphics (publishedVersion)
- Funders
- Division of Information and Intelligent Systems (CNFS-0406415IIS-0612231CCF-0702672)
- National Science Foundation (CNFS-0406415IIS-0612231CCF-0702672)
- Division of Computing and Communication Foundations (CNFS-0406415IIS-0612231CCF-0702672)
- 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 › Image Processing and 3D Reconstruction
- Keywords
- point matching, surface matching, Möbius transformations, isometries, transport distance, partial isometries
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
