skip to main content
research-article

geoTangle: Interactive Design of Geodesic Tangle Patterns on Surfaces

Published:29 November 2021Publication History
Skip Abstract Section

Abstract

Tangles are complex patterns, which are often used to decorate the surface of real-world artisanal objects. They consist of arrangements of simple shapes organized into nested hierarchies, obtained by recursively splitting regions to add progressively finer details. In this article, we show that 3D digital shapes can be decorated with tangles by working interactively in the intrinsic metric of the surface. Our tangles are generated by the recursive application of only four operators, which are derived from tracing the isolines or the integral curves of geodesics fields generated from selected seeds on the surface. Based on this formulation, we present an interactive application that lets designers model complex recursive patterns directly on the object surface without relying on parametrization. We reach interactive speed on meshes of a few million triangles by relying on an efficient approximate graph-based geodesic solver.

Skip Supplemental Material Section

Supplemental Material

REFERENCES

  1. Adikusuma Y. Y., Fang Z., and He Y.. 2020. Fast construction of discrete geodesic graphs. ACM Trans. Graph, 39, 2 (2020), 114. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Adobe. 2020. Substance Designer. (2020). Retrieved from https://www.substance3d.com.Google ScholarGoogle Scholar
  3. Autodesk. 2020. Mudbox. (2020). Retrieved from https://autodesk.com/mudbox.Google ScholarGoogle Scholar
  4. Bertsekas D. P.. 1998. Network Optimization: Continuous and Discrete Models. Athena Scientific, Belmont, MA.Google ScholarGoogle Scholar
  5. Bose P., Maheshwari A., Shu C., and Wuhrer S.. 2011. A survey of geodesic paths on 3D surfaces. Comput. Geom. Theory Appl. 44, 9 (2011), 486498. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Bronstein A. M., Bronstein M. M., and Kimmel R.. 2009. Numerical Geometry of Non-Rigid Shapes. Springer, New York. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Campen M., Heistermann M., and Kobbelt L.. 2013. Practical anisotropic geodesy. Comput. Graph. Forum 32, 13 (2013), 6371. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Campen M. and Kobbelt L.. 2011. Walking on broken mesh: Defect-tolerant geodesic distances and parameterizations. Comput. Graph. Forum 30, 2 (2011), 623632.Google ScholarGoogle ScholarCross RefCross Ref
  9. Campen M., Shen H., Zhou J., and Zorin D.. 2020. Seamless parametrization with arbitrary cones for arbitrary genus. ACM Trans. Graph. 39, 1 (2020), 2:1–2:19. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Carra E., Santoni C., and Pellacini F.. 2019. Grammar-based procedural animations for motion graphics. Comput. Graph. 78 (2019), 97107.Google ScholarGoogle ScholarCross RefCross Ref
  11. Chen J. and Han Yi. 1990. Shortest paths on a polyhedron. In 6th Annual Symposium on Computational Geometry.Association for Computing Machinery, New York, NY, 360369. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Chen W., Zhang X., Xin S., Xia Y., Lefebvre S., and Wang W.. 2016. Synthesis of filigrees for digital fabrication. ACM Trans. Graph. 35, 4 (2016), 113. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Crane K., Livesu M., Puppo E., and Qin Y.. 2020. A Survey of Algorithms for Geodesic Paths and Distances. arxiv:cs.GR/2007.10430.Google ScholarGoogle Scholar
  14. Crane K., Weischedel C., and Wardetzky M.. 2013. Geodesics in heat: A new approach to computing distance based on heat flow. ACM Trans. Graph. 32, 5 (2013), 152:1–152:11. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Denning J. D., Kerr W. B., and Pellacini F.. 2011. MeshFlow: Interactive visualization of mesh construction sequences. ACM Trans. Graph. 30, 4 (2011), 66:1–66:8. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Denning J. D., Tibaldo V., and Pellacini F.. 2015. 3DFlow: Continuous summarization of mesh editing workflows. ACM Trans. Graph. 34, 4 (2015), 140:1–140:9. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Ebert D., Musgrave K., Peachey D., Perlin K., and Worley S.. 2002. Texturing and Modeling: A Procedural Approach (3rd ed.). Morgan Kaufmann, San Francisco, CA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Eldar Y., Lindenbaum M., Porat M., and Zeevi Y. Y.. 1997. The farthest point strategy for progressive image sampling. Trans. Image Process. 6, 9 (1997), 13051315. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Graichen M., Izraelevitz J., and Scott M. L.. 2016. An unbounded nonblocking double-ended queue. In 45th International Conference on Parallel Processing (ICPP). 217226.Google ScholarGoogle ScholarCross RefCross Ref
  20. Herholz Philipp and Alexa Marc. 2018. Factor once: Reusing Cholesky factorizations on sub-meshes. ACM Trans. Graph. 37 (2018), 230:1–230:9. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Herholz P., Davis T. A., and Alexa M.. 2017a. Localized solutions of sparse linear systems for geometry processing. ACM Trans. Graph. 36, 6 (2017), 183:1–183:8. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Herholz P., Haase F., and Alexa M.. 2017b. Diffusion diagrams: Voronoi cells and centroids from diffusion. Comput. Graph. Forum 36, 2 (2017), 163175. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Jacobson A.. 2021. gptoolbox. Retrieved from https://mathworks.com/matlabcentral/fileexchange/49692-gptoolbox.Google ScholarGoogle Scholar
  24. Jiang C., Tang C., Vaxman A., Wonka P., and Pottmann H.. 2015. Polyhedral patterns. ACM Trans. Graph. 34, 6 (2015), 112. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Kimmel R. and Sethian J. A.. 1998. Computing geodesic paths on manifolds. Proc. Natl. Acad. Sci. 89, 15 (1998), 84318435.Google ScholarGoogle ScholarCross RefCross Ref
  26. Lanthier M., Maheshwari A., and Sack J.-R.. 1997. Approximating weighted shortest paths on polyhedral surfaces. In ACM Symposium on Computational Geometry. Association for Computing Machinery, New York, NY, 274283. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Lanthier M., Maheshwari A., and Sack J.-R.. 2001. Approximating shortest paths on weighted polyhedral surfaces. Algorithmica 30, 4 (2001), 527562.Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Levi Z.. 2021. Direct seamless parametrization. ACM Trans. Graph. 40, 1 (2021), 6:1–6:14. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Li M., Kaufman D. M., Kim V. G., Solomon J., and Sheffer A.. 2018. OptCuts: Joint optimization of surface cuts and parameterization. ACM Trans. Graph. 37, 6 (2018), 247:1–247:13. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Li Y., Bao F., Zhang E., Kobayashi Y., and Wonka P.. 2011. Geometry synthesis on surfaces using field-guided shape grammars. IEEE Trans. Vis. Comp. Graph. 17, 2 (2011), 231243. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Liu L., Zhang L., Xu Y., Gotsman C., and Gortler S. J.. 2008. A local/global approach to mesh parameterization. Comput. Graph. Forum 27, 6 (2008), 14951504. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Loi H., Hurtut T., Vergne R., and Thollot J.. 2017. Programmable 2D arrangements for element texture design. ACM Trans. Graph. 36, 3 (2017), 27:1–27:17. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Longay S., Runions A., Boudon F., and Prusinkiewicz P.. 2012. TreeSketch: Interactive procedural modeling of trees on a tablet. In EG Symposium on Sketch-based Interfaces and Modeling. The Eurographics Association, 107120. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Mitchell Joseph S. B., Mount David M., and Papadimitriou Christos H.. 1987. The discrete geodesic problem. SIAM J. Comput. 16, 4 (Aug. 1987), 647668. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Orzan A., Bousseau A., Winnemöller H., Barla P., Thollot J., and Salesin D.. 2008. Diffusion curves: A vector representation for smooth-shaded images. ACM Trans. Graph. 27, 3 (2008), 92:1–92:8. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Paoluzzi A., Bernardini F., Cattani C., and Ferrucci V.. 1993. Dimension-independent modeling with simplicial complexes. ACM Trans. Graph. 12, 1 (1993), 56102. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Pilgway. 2019. 3D-Coat. Retrieved from https://3dcoat.com.Google ScholarGoogle Scholar
  38. Pixologic. 2021. ZBrush. Retrieved from https://pixologic.com/zbrush/features/overview/.Google ScholarGoogle Scholar
  39. Poranne R., Tarini M., Huber S., Panozzo D., and Sorkine-Hornung O.. 2017. Autocuts: Simultaneous distortion and cut optimization for UV mapping. ACM Trans. Graph. 36, 6 (2017), 215:1–215:11. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. Prada F., Kazhdan M., Chuang M., and Hoppe H.. 2018. Gradient-domain processing within a texture atlas. ACM Trans. Graph. 37, 4 (2018), 154:1–154:14. Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. Qin Y., Han X., Yu H., Yu Y., and Zhang J.. 2016. Fast and exact discrete geodesic computation based on triangle-oriented wavefront propagation. ACM Trans. Graph. 35, 4 (2016), 125:1–125:13. Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. Calla L. A. Romero, Perez L. J. Fuentes, and Montenegro A. A.. 2019. A minimalistic approach for fast computation of geodesic distances on triangular meshes. Comput. Graph. 84 (2019), 7792.Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Santoni C., Calabrese C., Renzo F. Di, and Pellacini F.. 2016. SculptStat: Statistical analysis of digital sculpting workflows. arxiv:1601.07765Google ScholarGoogle Scholar
  44. Santoni C. and Pellacini F.. 2016. gTangle: A grammar for the procedural generation of tangle patterns. ACM Trans. Graph. 35, 6 (2016), 182:1–182:11. Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. Sawhney R. and Crane K.. 2017. Boundary first flattening. ACM Trans. Graph. 37, 1 (2017), 114. Google ScholarGoogle ScholarDigital LibraryDigital Library
  46. Schlick C.. 1994. Fast alternatives to Perlin’s bias and gain functions. In Graphics Gems IV, Heckbert P. S. (Ed.). Academic Press, Amsterdam, the Netherlands, 401403. Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. Schmid J., Senn M. S., Gross M., and Sumner R. W.. 2011. Overcoat: An implicit canvas for 3D painting. ACM Trans. Graph. 30, 4 (2011), 28:1–28:10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  48. Schwarz M. and Wonka P.. 2015. Practical grammar-based procedural modeling of architecture. In SIGGRAPH Asia 2015 Courses. Association for Computing Machinery, New York, NY. Google ScholarGoogle ScholarDigital LibraryDigital Library
  49. Sendik O. and Cohen-Or D.. 2017. Deep correlations for texture synthesis. ACM Trans. Graph. 36, 5 (2017), 161:1–161:15. Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. Sharp N. and Crane K.. 2020. You can find geodesic paths in triangle meshes by just flipping edges. ACM Trans. Graph. 39, 6 (2020), 249:1–249:15. Google ScholarGoogle ScholarDigital LibraryDigital Library
  51. Shi L., Li B., Hašan M., Sunkavalli K., Boubekeur T., Mech R., and Matusik W.. 2020. MATch: Differentiable material graphs for procedural material capture. ACM Trans. Graph. 39, 6 (2020), 115. Google ScholarGoogle ScholarDigital LibraryDigital Library
  52. Tao J., Zhang J., Deng B., Fang Z., Peng Y., and He Y.. 2021. Parallel and scalable heat methods for geodesic distance computation. IEEE Trans. Pattern Analysis Mach. Intell. 43 (2021), 579594.Google ScholarGoogle ScholarDigital LibraryDigital Library
  53. Vaxman A., Campen M., Diamanti O., Bommes D., Hildebrandt K., Ben-Chen M., and Panozzo D.. 2017. Directional field synthesis, design, and processing. In ACM SIGGRAPH 2017 Courses. Association for Computing Machinery, New York, NY. Google ScholarGoogle ScholarDigital LibraryDigital Library
  54. Wang X., Fang Z., Wu J., Xin S.-Q., and He Y.. 2017. Discrete geodesic graph (DGG) for computing geodesic distances on polyhedral surfaces. Comput.-aided Geom. Des. 52, C (2017), 262284. Google ScholarGoogle ScholarDigital LibraryDigital Library
  55. Wei Li-Yi, Lefebvre Sylvain, Kwatra Vivek, and Turk Greg. 2009. State of the art in example-based texture synthesis. In Eurographics State of the Art Report. The Eurographics Association, Geneve, Switzerland.Google ScholarGoogle Scholar
  56. Weiler K.. 1985. Edge-based data structures for solid modeling in curved-surface environments. IEEE Comput. Graph. Applic. 5, 1 (1985), 2140. Google ScholarGoogle ScholarDigital LibraryDigital Library
  57. Xu Pengfei, Fu Hongbo, Zheng Youyi, Singh Karan, Huang Hui, and Tai Chiew-Lan. 2018. Model-guided 3D sketching. IEEE Trans. Vis. Comput. Graph. 25, 10 (2018), 29272939.Google ScholarGoogle ScholarCross RefCross Ref
  58. Ying Xiang, Huang Caibao, Fu Xuzhou, He Ying, Yu Ruiguo, Wang Jianrong, and Yu Mei. 2019. Parallelizing discrete geodesic algorithms with perfect efficiency. Comput.-aided Des. 115 (Oct. 2019), 161171.Google ScholarGoogle ScholarDigital LibraryDigital Library
  59. Ying X., Wang X., and He Y.. 2013. Saddle vertex graph (SVG): A novel solution to the discrete geodesic problem. ACM Trans. Graph. 32, 6 (2013), 170:1–170:12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  60. Zhou Y., Zhu Z., Bai X., Lischinski D., Cohen-Or D., and Huang H.. 2018. Non-stationary texture synthesis by adversarial expansion. ACM Trans. Graph. 37, 4 (2018), 49:1–49:13.Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. geoTangle: Interactive Design of Geodesic Tangle Patterns on Surfaces

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      • Published in

        cover image ACM Transactions on Graphics
        ACM Transactions on Graphics  Volume 41, Issue 2
        April 2022
        197 pages
        ISSN:0730-0301
        EISSN:1557-7368
        DOI:10.1145/3501283
        Issue’s Table of Contents

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 29 November 2021
        • Revised: 1 September 2021
        • Accepted: 1 September 2021
        • Received: 1 May 2021
        Published in tog Volume 41, Issue 2

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article
        • Refereed

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      Full Text

      View this article in Full Text.

      View Full Text

      HTML Format

      View this article in HTML Format .

      View HTML Format