A Survey on Data-driven Dictionary-based Methods for 3D Modeling

Thibault Lescoat, Maks Ovsjanikov, Pooran Memari, Jean-Marc Thiery, Tamy Boubekeur
Computer Graphics Forum - EUROGRAPHICS 2018 STAR

3D Dictionary STAR

Abstract

Dictionaries are very useful objects for data analysis, as they enable a compact representation of large sets of objects through the combination of atoms. Dictionary-based techniques have also particularly benefited from the recent advances in machine learning, which has allowed for data-driven algorithms to take advantage of the redundancy in the input dataset and discover relations between objects without human supervision or hard-coded rules. Despite the success of dictionary-based techniques on a wide range of tasks in geometric modeling and geometry processing, the literature is missing a principled state-of-the-art of the current knowledge in this field. To fill this gap, we provide in this survey an overview of data-driven dictionary-based methods in geometric modeling. We structure our discussion by application domain: surface reconstruction, compression, and synthesis. Contrary to previous surveys, we place special emphasis on dictionary-based methods suitable for 3D data synthesis, with applications in geometric modeling and design. Our ultimate goal is to enlight the fact that these techniques can be used to combine the data-driven paradigm with design intent to synthesize new plausible objects with minimal human intervention. This is the main motivation to restrict the scope of the present survey to techniques handling point clouds and meshes, making use of dictionaries whose definition depends on the input data, and enabling shape reconstruction or synthesis through the combination of atoms.

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Bibtex

@article{Lescoat:2018:3DDictSTAR,
 author = {Thibault Lescoat and Maks Ovsjanikov and Pooran Memari and Jean-Marc Thiery and Tamy Boubekeur},
 title = {A Survey on Data-driven Dictionary-based Methods for 3D Modeling},
 journal = {Computer Graphics Forum (Proc. EUROGRAPHICS 2018 STAR)},
 volume = {37},
 number = {2},
 year = {2018},
} 

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Articulated-motion-aware sparse localized decomposition.
Computer Graphics Forum (2016), n/a–n/a.
[WSK*15]
Wu Z., Song S., Khosla A., Yu F., Zhang L., Tang X., Xiao J.
3d shapenets: A deep representation for volumetric shapes.
In 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (June 2015), pp. 1912–1920.
[WZX*16]
Wu J., Zhang C., Xue T., Freeman W. T., Tenenbaum J. B.
Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling.
CoRR abs/1610.07584 (2016).
[XfT16]
Xie H., feng Tong R.
Image meshing via hierarchical optimization.
Frontiers of Information Technology & Electronic Engineering 17, 1 (2016), 32–40.
[XKHK15]
Xu K., Kim V. G., Huang Q., Kalogerakis E.
Data-driven shape analysis and processing.
CoRR abs/1502.06686 (2015).
[XSX*14]
Xu W., Shi Z., Xu M., Zhou K., Wang J., Zhou B., Wang J., Yuan Z.
Transductive 3d shape segmentation using sparse reconstruction.
Computer Graphics Forum 33, 5 (2014), 107–115.
[XWY*16]
Xu L., Wang R., Yang Z., Deng J., Chen F., Liu L.
Surface approximation via sparse representation and parameterization optimization.
Computer Aided Design 78, C (2016), 179–187.
[XWZ*15]
Xu L., Wang R., Zhang J., Yang Z., Deng J., Chen F., Liu L.
Survey on sparsity in geometric modeling and processing.
Graphical Models 82 (2015), 160 – 180.
[XXLX14]
Xie Z., Xu K., Liu L., Xiong Y.
3d shape segmentation and labeling via extreme learning machine.
Computer Graphics Forum 33, 5 (2014), 85–95.
[XXM*13]
Xie X., Xu K., Mitra N. J., Cohen-Or D., Gong W., Su Q., Chen B.
Sketch-to-design: Context-based part assembly.
Computer Graphics Forum (2013).
[XZCOC12]
Xu K., Zhang H., Cohen-Or D., Chen B.
Fit and diverse: Set evolution for inspiring 3d shape galleries.
ACM Transactions on Graphics (Proc. Siggraph) 31, 4 (2012), 57:1–57:10.
[XZWB05]
Xu D., Zhang H., Wang Q., Bao H.
Poisson shape interpolation.
In Proceedings of the 2005 ACM Symposium on Solid and Physical Modeling (New York, NY, USA, 2005), SPM '05, pp. 267–274.
[XZZ*14]
Xiong S., Zhang J., Zheng J., Cai J., Liu L.
Robust surface reconstruction via dictionary learning.
ACM Transactions on Graphics (Proc. Siggraph Asia) 33 (2014).
[YK14]
Yumer M. E., Kara L. B.
Co-constrained handles for deformation in shape collections.
ACM Transactions on Graphics (Proc. Siggraph Asia) 33, 6 (2014), 187:1–187:11.
[YLÖ*16]
Yoon Y.-J., Lelidis A., Öztireli A. C., Hwang J.-M., Gross M., Choi S.-M.
Geometry representations with unsupervised feature learning.
vol. 00, pp. 137–142.