“Capture and modeling of non-linear heterogeneous soft tissue” by Bickel, Bächer, Otaduy, Matusik, Pfister, et al. …

  • ©Bernd Bickel, Moritz Bächer, Miguel A. Otaduy, Wojciech Matusik, Hanspeter Pfister, and Markus Gross

Conference:


Type:


Title:

    Capture and modeling of non-linear heterogeneous soft tissue

Presenter(s)/Author(s):



Abstract:


    This paper introduces a data-driven representation and modeling technique for simulating non-linear heterogeneous soft tissue. It simplifies the construction of convincing deformable models by avoiding complex selection and tuning of physical material parameters, yet retaining the richness of non-linear heterogeneous behavior. We acquire a set of example deformations of a real object, and represent each of them as a spatially varying stress-strain relationship in a finite-element model. We then model the material by non-linear interpolation of these stress-strain relationships in strain-space. Our method relies on a simple-to-build capture system and an efficient run-time simulation algorithm based on incremental loading, making it suitable for interactive computer graphics applications. We present the results of our approach for several non-linear materials and biological soft tissue, with accurate agreement of our model to the measured data.

References:


    1. Allen, B., Curless, B., and Popović, Z. 2002. Articulated body deformation from range scan data. ACM Trans. Graph. 21, 3, 612–619. Google ScholarDigital Library
    2. Bathe, K.-J. 1995. Finite Element Procedures. Prentice-Hall.Google Scholar
    3. Becker, M., and Teschner, M. 2007. Robust and efficient estimation of elasticity parameters using the linear finite element method. In SimVis, 15–28.Google Scholar
    4. Bergeron, P., and Lachapelle, P., 1985. Controlling facial expression and body movements in the computer generated short “Tony de Peltrie”. Siggraph Course Notes.Google Scholar
    5. Bickel, B., Lang, M., Botsch, M., Otaduy, M. A., and Gross, M. 2008. Pose-space animation and transfer of facial details. In Proc. of the ACM SIGGRAPH / Eurographics Symposium on Computer Animation, 57–66. Google ScholarDigital Library
    6. Blanz, V., Basso, C., Poggio, T., and Vetter, T. 2003. Re-animating faces in images and video. Computer Graphics Forum 22, 3 (Sept.), 641–650.Google ScholarCross Ref
    7. Botsch, M., and Sorkine, O. 2008. On linear variational surface deformation methods. IEEE Transactions on Visualization and Computer Graphics (TVCG) 14, 1, 213–230. Google ScholarDigital Library
    8. Buehler, C., Bosse, M., McMillan, L., Gortler, S., and Cohen, M. 2001. Unstructured lumigraph rendering. In Proc. of ACM SIGGRAPH, ACM, 425–432. Google ScholarDigital Library
    9. Burion, S., Conti, F., Petrovskaya, A., Baur, C., and Khatib, O. 2008. Identifying physical properties of deformable objects by using particle filters. In Proc. of the International Conference on Robotics and Automation, 1112–1117.Google Scholar
    10. Capell, S., Burkhart, M., Curless, B., Duchamp, T., and Popović, Z. 2005. Physically based rigging for deformable characters. In ACM SIGGRAPH/Eurographics Symposium on Computer Animation, 301–310. Google ScholarDigital Library
    11. Carr, J. C., Beatson, R. K., Cherrie, J. B., Mitchell, T. J., Fright, W. R., McCallum, B. C., and Evans, T. R. 2001. Reconstruction and representation of 3D objects with radial basis functions. In Proc. of ACM SIGGRAPH, 67–76. Google ScholarDigital Library
    12. DiLorenzo, P., Zordan, V., and Sanders, B. 2008. Laughing Out Loud: Control for modeling anatomically inspired laughter using audio. ACM Trans. Graph. (Proc. of ACM SIGGRAPH Asia) 27, 5. Google ScholarDigital Library
    13. Galoppo, N., Otaduy, M. A., Moss, W., Sewall, J., Curtis, S., and Lin, M. C. 2009. Controlling deformable material with dynamic morph targets. In ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games. Google ScholarDigital Library
    14. Hart, E. W. 1967. Theory of the tensile test. Acta Metallurgica 15, 351–355.Google ScholarCross Ref
    15. Hughes, T. J. R. 2000. The Finite Element Method. Linear Static and Dynamic Finite Element Analysis. Dover Publications.Google Scholar
    16. James, D. L., and Pai, D. K. 1999. ArtDefo: Accurate real time deformable objects. In Proc. of ACM SIGGRAPH, ACM Press/Addison-Wesley Publishing Co., 65–72. Google ScholarDigital Library
    17. Kajberg, J., and Lindkvist, G. 2004. Characterisation of materials subjected to large strains by inverse modelling based on in-plane displacement fields. International Journal of Solids and Structures 41, 13, 3439–3459.Google ScholarCross Ref
    18. Kauer, M., Vuskovic, V., Dual, J., Szekely, G., and Bajka, M. 2002. Inverse finite element characterization of soft tissues. Medical Image Analysis 6, 3, 257–287.Google ScholarCross Ref
    19. Kaufmann, P., Martin, S., Botsch, M., and Gross, M. 2008. Flexible simulation of deformable models using discontinuous galerkin fem. Proceedings of the ACM SIGGRAPH / Eurographics Symposium on Computer Animation, 105–115. Google ScholarDigital Library
    20. Kim, T.-Y., and Vendrovsky, E. 2008. Drivenshape – a data-driven approach to shape deformation. In Proc. of the ACM SIGGRAPH / Eurographics Symposium on Computer Animation. Google ScholarDigital Library
    21. Koch, R. M., Gross, M. H., Carls, F. R., von Büren, D. F., Fankhauser, G., and Parish, Y. 1996. Simulating facial surgery using finite element methods. In Proc. of ACM SIGGRAPH, 421–428. Google ScholarDigital Library
    22. Kry, P. G., and Pai, D. K. 2006. Interaction capture and synthesis. ACM Trans. Graph. (Proc. of ACM SIGGRAPH) 25, 3, 872–880. Google ScholarDigital Library
    23. Lang, J., Pai, D. K., and Woodham, R. J. 2002. Acquisition of elastic models for interactive simulation. International Journal of Robotics Research 21, 8, 713–733.Google ScholarCross Ref
    24. Lee, S.-H., and Terzopoulos, D. 2006. Heads up!: Biomechanical modeling and neuromuscular control of the neck. ACM Trans. Graph. (Proc. of ACM SIGGRAPH) 25, 3. Google ScholarDigital Library
    25. Levenberg, K. 1944. A method for the solution of certain non-linear problems in least squares. The Quarterly of Applied Mathematics, 2, 164–168.Google ScholarCross Ref
    26. Lewis, J. P., Cordner, M., and Fong, N. 2000. Pose space deformation: A unified approach to shape interpolation and skeleton-driven deformation. In Proc. of ACM SIGGRAPH, 165–172. Google ScholarDigital Library
    27. Ma, W.-C., Jones, A., Chiang, J.-Y., Hawkins, T., Frederiksen, S., Peers, P., Vukovic, M., Ouhyoung, M., and Debevec, P. 2008. Facial performance synthesis using deformation-driven polynomial displacement maps. ACM Trans. Graph. (Proc. of ACM SIGGRAPH Asia) 27, 5. Google ScholarDigital Library
    28. Magnenat-Thalmann, N., Kalra, P., Lévêque, J. L., Bazin, R., Batisse, D., and Queleux, B. 2002. A computational skin model: fold and wrinkle formation. IEEE Trans. on Information Technology in Biomedicine 6, 4, 317–323. Google ScholarDigital Library
    29. Matusik, W., Pfister, H., Brand, M., and McMillan, L. 2003. A data-driven reflectance model. ACM Transactions on Graphics (Proc. of ACM SIGGRAPH) 22, 3, 759–770. Google ScholarDigital Library
    30. Müller, M., and Gross, M. 2004. Interactive virtual materials. In GI ’04: Proceedings of Graphics Interface 2004, Canadian Human-Computer Communications Society, School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada, 239–246. Google ScholarDigital Library
    31. Nava, A., Mazza, E., Kleinermann, F., Avis, N. J., and McClure, J. 2003. Determination of the mechanical properties of soft human tissues through aspiration experiments. In Proc. of MICCAI, 222–229.Google ScholarCross Ref
    32. Nealen, A., Mller, M., Keiser, R., Boxerman, E., and Carlson, M. 2006. Physically based deformable models in computer graphics. Computer Graphics Forum 25, 4 (Dec.), 809–836.Google ScholarCross Ref
    33. Ogden, R. W. 1997. Non-Linear Elastic Deformations. Courier Dover Publications.Google Scholar
    34. Ottensmeyer, M. P., and Salisbury Jr., J. K. 2004. In-vivo data acquisition instrument for solid organ mechanical property measurement. In Proc. of MICCAI, 975–982. Google ScholarDigital Library
    35. Pai, D. K., van den Doel, K., James, D. L., Lang, J., Lloyd, J. E., Richmond, J. L., and Yau, S. H. 2001. Scanning physical interaction behavior of 3d objects. In Proceedings of ACM SIGGRAPH, 87–96. Google ScholarDigital Library
    36. Park, S. I., and Hodgins, J. K. 2006. Capturing and animating skin deformation in human motion. ACM Transactions on Graphics (Proc. of ACM SIGGRAPH) 25, 3. Google ScholarDigital Library
    37. Park, S. I., and Hodgins, J. K. 2008. Data-driven modeling of skin and muscle deformation. ACM Transactions on Graphics (Proc. of ACM SIGGRAPH) 27, 3. Google ScholarDigital Library
    38. Schnur, D. S., and Zabaras, N. 1992. An inverse method for determining elastic material properties and a material interface. International Journal for Numerical Methods in Engineering 33, 10, 2039–2057.Google ScholarCross Ref
    39. Schoner, J. L., Lang, J., and Seidel, H.-P. 2004. Measurement-based interactive simulation of viscoelastic solids. Computer Graphics Forum (Proc. Eurographics) 23, 3, 547–556.Google ScholarCross Ref
    40. Sifakis, E., Neverov, I., and Fedkiw, R. 2005. Automatic determination of facial muscle activations from sparse motion capture marker data. ACM Transactions on Graphics (Proc. of ACM SIGGRAPH) 24, 3, 417–425. Google ScholarDigital Library
    41. Sloan, P.-P. J., Rose, III, C. F., and Cohen, M. F. 2001. Shape by example. In I3D ’01: Proceedings of the 2001 symposium on Interactive 3D graphics, ACM, New York, NY, USA, 135–143. Google ScholarDigital Library
    42. Sueda, S., Kaufman, A., and Pai, D. K. 2008. Musculotendon simulation for hand animation. ACM Trans. Graph. (Proc. SIGGRAPH) 27, 3. Google ScholarDigital Library
    43. Sumner, R. W., Zwicker, M., Gotsman, C., and Popović, J. 2005. Mesh-based inverse kinematics. In ACM Trans. on Graphics (Proc. of ACM SIGGRAPH), vol. 24, 488–495. Google ScholarDigital Library
    44. Teran, J., Sifakis, E., Blemker, S., Ng Thow Hing, V., Lau, C., and Fedkiw, R. 2005. Creating and simulating skeletal muscle from the visible human data set. IEEE TVCG 11, 317–328. Google ScholarDigital Library
    45. Terzopoulos, D., Platt, J., Barr, A., and Fleischer, K. 1987. Elastically deformable models. In Proc. of ACM SIGGRAPH 87, 205–214. Google ScholarDigital Library
    46. Terzopoulus, D., and Waters, K. 1993. Analysis and synthesis of facial image sequences using physical and anatomical models. IEEE Trans. PAMI 14 (June), 569–579. Google ScholarDigital Library
    47. Toledo, S., Chen, D., and Rotkin, V. 2003. Taucs: A library for sparse linear solvers.Google Scholar
    48. Zhang, H. 2004. Discrete combinatorial laplacian operators for digital geometry processing. In Proc. of SIAM Conference on Geometric Design and Computing, Nashboro Press, 575–592.Google Scholar
    49. Zordan, V., Celly, B., Chiu, B., and Dilorenzo, P. C. 2004. Breathe easy: Model and control of human respiration for computer animation. In Proc. of the ACM SIGGRAPH / Eurographics Symposium on Computer Animation, 29–38. Google ScholarDigital Library


ACM Digital Library Publication: