Skip to main content
Log in

Estimating material properties of deformable objects by considering global object behavior in video streams

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

    We’re sorry, something doesn't seem to be working properly.

    Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.

Abstract

One of the crucial components in improving simulation quality in physics-based animation of deformable object is finding proper material properties that define the movement upon external excitation. Most work in the estimation of material properties for highly deformable objects involves applying localized force to a point on the object’s surface with mechanical devices and measuring the displacement of the surface at the contact point and surrounding points. While understanding this localized behavior provides a step towards accurately simulating objects with known material properties, an understanding of the global behavior of the object undergoing deformation is more important for many practical applications. This paper describes both the computer vision based techniques for tracking global position information of moving deformable objects from a video stream and the optimization routine for estimating the elasticity parameters of a mass-spring simulation. The collected data is the object’s surface node position of object over time which is used to a data-driven simulation of that object to match the behavior of a virtual object to the corresponding real one. This paper demonstrates that estimating material properties of highly elastic objects by matching the global behavior of the object in a video is possible with the proposed method and the experimental results show that the captured and simulated motions are well matched each other.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Becker M (2007) Robust and efficient estimation of elasticity parameters using the linear finite element method. Proc Simul Vis 15–28

  2. Bhat K, Twigg C, Hodgins J (2003) Estimating cloth simulation parameters from video. Proceedings of the 2003 ACM SIGGRAPH/Eurographics Symposium on Computer Animation. Eurographics Association, pp 37–51

  3. Bickel B, Botsch M, Angst R, Matusik W, Otaduy M, Pfister H, Gross M (2007) Multi-scale capture of facial geometry and motion. ACM Trans Graph (TOG) 26(3):33

    Article  Google Scholar 

  4. Bickel B, Lang M, Botsch M (2008) Pose-space animation and transfer of facial details. Proceedings of the 2008 ACM SIGGRAPHEurographics Symposium on Computer Animation, Eurographics Association, pp 57–66

  5. Bradley D, Boubekeur T, Heidrich W (2008) Accurate multi-view reconstruction using robust binocular stereo and surface meshing. IEEE Conf Comput Vis Pattern Recognit 1–8:2008

    Google Scholar 

  6. Bradski G (2000) The OpenCV Library. Dr. Dobb’s Journal of Software Tools

  7. Chaudhary A, Vatwani K, Agrawal T, Raheja JL (2012) A vision-based method to find fingertips in a closed hand. J Inf Process Syst 8(3):399–408

    Article  Google Scholar 

  8. Erwin C. Bullet Physics Library. [Online]. https://code.google.com/p/bullet/

  9. Frank B, Schmedding R (2010) Learning the elasticity parameters of deformable objects with a manipulation robot. Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on. IEEE, pp 1877–1883

  10. Gilles B, Bousquet G, Faure F, Pai DK (2011) Frame-based elastic models. ACM Trans Graph (TOG) 30(2):15

    Article  Google Scholar 

  11. Jeon JH, Choi M-H, Hong M (2012) Enhanced FFD-AABB collision algorithm for deformable objects. J Inf Process Syst 8(4):713–720

    Article  Google Scholar 

  12. Kim J, Yoon S, Lee Y (2014) Trivariate B-spline Approximation of Spherical Solid Objects. J Inf Process Syst 10(1):23–35

  13. Kunitomo S, Nakamura S, Morishima S (2010) Optimization of cloth simulation parameters by considering static and dynamic features. ACM SIGGRAPH 2010 Posters 15:2010

    Google Scholar 

  14. Lang J (2001) Deformable model acquisition and validation. PhD Thesis, University of British Columbia

  15. Miguel E, Bradley D, Thomaszewski B, Bickel B, Matusik W, Otaduy MA, Marschner S (2012) Data-driven estimation of cloth simulation models. Comput Graph Forum 31(2):519–528

    Article  Google Scholar 

  16. Otaduy M, Bickel B, Bradley D, Wang H (2012) Data-driven simulation methods in computer graphics: cloth, tissue and faces. ACM SIGGRAPH 2012 Courses

  17. Sebastian P, Voon YV, Comley R (2010) Colour space effect on tracking in video surveillance. Int J Electr Eng Inf 2(4):298–312

    Article  Google Scholar 

  18. Shah M (1997) Fundamentals of computer vision. University of Central Florida, Orlando

    Google Scholar 

  19. Si H (2004) TetGen: a quality tetrahedral mesh generator and three-dimensional delaunay triangulator, version 1.3, software. Weierstrass Inst. for Appl. Anal. and Stochastics

  20. Syllebranque C, Boivin S (2008) Estimation of mechanical parameters of deformable solids from videos. Vis Comput 4(11):963–972

    Article  Google Scholar 

  21. Wang H, O’Brien J, Ramamoorthi R (2011) Data-driven elastic models for cloth: modeling and measurement. ACM Trans Graph (TOG) 30(4):1–11

    Google Scholar 

Download references

Acknowledgments

This work was partially supported by the Soonchunhyang University Research Fund (No. 20130575).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Min Hong.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Choi, MH., Wilber, S.C. & Hong, M. Estimating material properties of deformable objects by considering global object behavior in video streams. Multimed Tools Appl 74, 3361–3375 (2015). https://doi.org/10.1007/s11042-014-1995-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-014-1995-1

Keywords

Navigation