research-article

Exploration of continuous variability in collections of 3D shapes

Authors:

Maks Ovsjanikov,

Leonidas Guibas,

Niloy J. MitraAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 30, Issue 4

Article No.: 33, Pages 1 - 10

https://doi.org/10.1145/2010324.1964928

Published: 25 July 2011 Publication History

Abstract

As large public repositories of 3D shapes continue to grow, the amount of shape variability in such collections also increases, both in terms of the number of different classes of shapes, as well as the geometric variability of shapes within each class. While this gives users more choice for shape selection, it can be difficult to explore large collections and understand the range of variations amongst the shapes. Exploration is particularly challenging for public shape repositories, which are often only loosely tagged and contain neither point-based nor part-based correspondences. In this paper, we present a method for discovering and exploring continuous variability in a collection of 3D shapes without correspondences. Our method is based on a novel navigation interface that allows users to explore a collection of related shapes by deforming a base template shape through a set of intuitive deformation controls. We also help the user to select the most meaningful deformations using a novel technique for learning shape variability in terms of deformations of the template. Our technique assumes that the set of shapes lies near a low-dimensional manifold in a certain descriptor space, which allows us to avoid establishing correspondences between shapes, while being rotation and scaling invariant. We present results on several shape collections taken directly from public repositories.

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References

[1]

Allen, B., Curless, B., and Popović, Z. 2003. The space of human body shapes: reconstruction and parameterization from range scans. In Proc. SIGGRAPH, 587--594.

[2]

Anguelov, D., Srinivasan, P., Koller, D., Thrun, S., Rodgers, J., and Davis, J. 2005. Scape: shape completion and animation of people. ACM SIGGRAPH 24 (July), 408--416.

Digital Library

[3]

Berner, A., Wand, M., Mitra, N. J., Mewes, D., and Seidel, H.-P. 2011. Shape analysis with subspace symmetries. CGF (Proc. EUROGRAPHICS) 30, 2, 277--286.

[4]

Blanz, V., and Vetter, T. 1999. A morphable model for the synthesis of 3d faces. In Proc. SIGGRAPH, 187--194.

[5]

Boutin, M., and Kemper, G. 2004. On reconstructing n-point configurations from the distribution of distances or areas. Advances in Applied Mathematics 32, 4, 709--735.

Digital Library

[6]

Chaudhuri, S., and Koltun, V. 2010. Data-driven suggestions for creativity support in 3d modeling. In ACM SIGGRAPH Asia, 183:1--183:10.

[7]

Chazal, F., Cohen Steiner, D., and Mérigot, Q. 2010. Geometric Inference for Measures based on Distance Functions. Research Report RR-6930, INRIA.

[8]

Cootes, T. F., Taylor, C. J., Cooper, D. H., and Graham, J. 1995. Active shape models -- their training and application. Comput. Vis. Image Underst. 61, 38--59.

Digital Library

[9]

Dryden, I., and Mardia, K. 1998. Statistical Shape Analysis. John Wiley & Sons.

[10]

Fisher, M., and Hanrahan, P. 2010. Context-based search for 3d models. In ACM SIGGRAPH Asia, 182:1--182:10.

[11]

Funkhouser, T., Kazhdan, M., Shilane, P., Min, P., Kiefer, W., Tal, A., Rusinkiewicz, S., and Dobkin, D. 2004. Modeling by example. ACM SIGGRAPH 23, 652--663.

Digital Library

[12]

Golovinskiy, A., and Funkhouser, T. 2009. Consistent segmentation of 3d models. Comput. Graph. 33 (June), 262--269.

Digital Library

[13]

Kalogerakis, E., Hertzmann, A., and Singh, K. 2010. Learning 3d mesh segmentation and labeling. In ACM SIGGRAPH, 102:1--102:12.

Digital Library

[14]

Kazhdan, M., Funkhouser, T., and Rusinkiewicz, S. 2003. Rotation invariant spherical harmonic representation of 3d shape descriptors. In Proc. SGP, 156--164.

Digital Library

[15]

Kilian, M., Mitra, N. J., and Pottmann, H. 2007. Geometric modeling in shape space. vol. 26, #64, 1--8.

[16]

Kim, M.-J., Kim, M.-H., and Shen, D. 2008. Learning-based deformation estimation for fast non-rigid registration. In CVPR workshop, 1--6.

[17]

Kokkinos, I., and Yuille, A. 2007. Unsupervised learning of object deformation models. In IEEE ICCV, 1--8.

[18]

Laga, H., Takahashi, H., and Nakajima, M. 2006. Spherical wavelet descriptors for content-based 3d model retrieval. In SMI, 15.

[19]

Mitra, N. J., Guibas, L., and Pauly, M. 2007. Symmetrization. In ACM SIGGRAPH, vol. 26, #63, 1--8.

[20]

Osada, R., Funkhouser, T., Chazelle, B., and Dobkin, D. 2002. Shape distributions. ACM TOG 21, 807--832.

Digital Library

[21]

Ovsjanikov, M., Bronstein, A. M., Bronstein, M. M., and Guibas, L. 2009. Shapegoogle: a computer vision approach for invariant shape retrieval. In ICCV workshop, NORDIA.

[22]

Saltel, E., 2008. INRIA Gamma team research database. http://www-roc.inria.fr/gamma/download/download.php.

[23]

Shapira, L., Shamir, A., and Cohen-Or, D. 2008. Consistent mesh partitioning and skeletonisation using the shape diameter function. Vis. Comput. 24, 249--259.

Digital Library

[24]

Sorkine, O., and Alexa, M. 2007. As-rigid-as-possible surface modeling. In Proc. SGP, 109--116.

Digital Library

[25]

Sumner, R. W., Zwicker, M., Gotsman, C., and Popović, J. 2005. Mesh-based inverse kinematics. ACM SIGGRAPH 24, 488--495.

Digital Library

[26]

van Kaick, O., Zhang, H., Hamarneh, G., and Cohen-Or, D. 2010. A survey on shape correspondence. Computer Graphics Forum.

[27]

Xu, K., Li, H., Zhang, H., Cohen-Or, D., Xiong, Y., and Cheng, Z.-Q. 2010. Style-content separation by anisotropic part scales. In ACM SIGGRAPH Asia, 184:1--184:10.

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https://dl.acm.org/doi/10.1145/3664647.3680798
Sutherland SEgger BTenenbaum J(2024)Building 3D Generative Models from Minimal DataInternational Journal of Computer Vision10.1007/s11263-023-01870-2132:2(555-580)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1007/s11263-023-01870-2
Koehl POrland H(2023)A Physicist’s View on Partial 3D Shape MatchingAlgorithms10.3390/a1607034616:7(346)Online publication date: 18-Jul-2023
https://doi.org/10.3390/a16070346
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Index Terms

Exploration of continuous variability in collections of 3D shapes
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Image and video acquisition
        3D imaging
  2. Computer graphics
    1. Animation
    2. Shape modeling
2. Theory of computation
  1. Randomness, geometry and discrete structures
    1. Computational geometry

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Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 30, Issue 4

July 2011

829 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/2010324

Issue’s Table of Contents

Copyright © 2011 ACM.

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Association for Computing Machinery

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Publication History

Published: 25 July 2011

Published in TOG Volume 30, Issue 4

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Cited By

Zhang SHuang JYue LZhang JLiu JLai YZhang SCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)SceneExpander: Real-Time Scene Synthesis for Interactive Floor Plan EditingProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3680798(6232-6240)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3680798
Sutherland SEgger BTenenbaum J(2024)Building 3D Generative Models from Minimal DataInternational Journal of Computer Vision10.1007/s11263-023-01870-2132:2(555-580)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1007/s11263-023-01870-2
Koehl POrland H(2023)A Physicist’s View on Partial 3D Shape MatchingAlgorithms10.3390/a1607034616:7(346)Online publication date: 18-Jul-2023
https://doi.org/10.3390/a16070346
Kodnongbua MJones BAhmad MKim VSchulz A(2023)ReparamCAD: Zero-shot CAD Re-Parameterization for Interactive ManipulationSIGGRAPH Asia 2023 Conference Papers10.1145/3610548.3618219(1-12)Online publication date: 10-Dec-2023
https://dl.acm.org/doi/10.1145/3610548.3618219
Hu JHui KLiu ZZhang HFu C(2023)CLIPXPlore: Coupled CLIP and Shape Spaces for 3D Shape ExplorationSIGGRAPH Asia 2023 Conference Papers10.1145/3610548.3618144(1-12)Online publication date: 10-Dec-2023
https://dl.acm.org/doi/10.1145/3610548.3618144
Pandey KChevalier FSingh K(2023)Juxtaform: interactive visual summarization for exploratory shape designACM Transactions on Graphics10.1145/359243642:4(1-14)Online publication date: 26-Jul-2023
https://dl.acm.org/doi/10.1145/3592436
Raganato APasi GMelzi S(2023)Attention And Positional Encoding Are (Almost) All You Need For Shape MatchingComputer Graphics Forum10.1111/cgf.1491242:5Online publication date: 10-Aug-2023
https://doi.org/10.1111/cgf.14912
Kim JMo KSung MWoo W(2023)Seg&Struct: The Interplay Between Part Segmentation and Structure Inference for 3D Shape Parsing2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)10.1109/WACV56688.2023.00128(1226-1235)Online publication date: Jan-2023
https://doi.org/10.1109/WACV56688.2023.00128
Zhang FFu QLiu YLi X(2023)Component-aware generative autoencoder for structure hybrid and shape completionGraphical Models10.1016/j.gmod.2023.101185129(101185)Online publication date: Oct-2023
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Chung JKim WYoo KLee HAdar EChang M(2022)TaleBrush: Sketching Stories with Generative Pretrained Language ModelsProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3501819(1-19)Online publication date: 29-Apr-2022
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