Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

On the simulation of expressional animation based on facial MoCap

  • Research Papers
  • Published:
Science China Information Sciences Aims and scope Submit manuscript

Abstract

MoCap (motion capture)-based animation is a hot issue in computer animation research currently. Based on the optical MoCap system, this paper proposes a novel cross-mapping based facial expression simulating method. To overcome the problem of the false upper and lower jaw correlation derived from the facial global RBF-based cross-mapping method, we construct a functional partition based RBF cross-mapping method. During model animating, enhanced markers are added and animated by our proposed skin motion mechanism. In addition, based on the enhanced markers, an improved RBF-based animating approach is raised to derive realistic facial animation. Further more, a pre-computing algorithm is presented to reduce computational cost for real-time simulation. The experiments proved that the method can not only map the MoCap data of one subject to different personalized faces but generate realistic facial animation.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Parke F I, Waters K. Computer Facial Animation. Massachusetts: A K Peters Ltd. 1996

    Google Scholar 

  2. Noh J, Neumann U. A Survey of Facial Modeling and Animation Techniques. Technical Report. California: University of Southern Californis, 1998

    Google Scholar 

  3. Deng Z, Noh J. Computer facial animation: a survey. In: Data-Driven 3D Facial Animation. London: Springer, 2007. 1–28

    Chapter  Google Scholar 

  4. Noh J, Neumann U. Expression cloning. In: Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques. New York: ACM, 2001. 277–288

    Google Scholar 

  5. Chai J, Mellon C, Hodgins J. Vision-based control of 3D facial animation. In: Eurographics/SIGGRAPH Symposium on Computer Animation. Switzerland: Eurographics Association Aire-la-Ville, 2003. 192–206

  6. Lorenzo M S, Edge J D, King S A, et al. Use and re-use of facial MoCap data. In: Proceedings of Vision, Video and Graphics. Switzerland: Eurographics Association Aire-la-Ville, 2003. 135–142

    Google Scholar 

  7. Edge J D, Snchez M A, Maddock S. Animating Speech from Motion Fragments. Technical Report CS-04-02. Department of Computer Science, University of Sheffield

  8. Havaldar P. Performance-driven facial animation. In: Proceedings of SIGGRAPH 2006 (course notes). New York: ACM, 2006. 23–42

    Google Scholar 

  9. Curio C, Breidt M, Vuong Q, et al. Semantic 3D motion retargeting for facial animation. In: ACM International Conference Proceeding Series. New York: ACM, 2006. 77–84

    Google Scholar 

  10. Deng Z, Chiang P, Fox P, et al. Animating blendshape faces by cross-mapping MoCap data. In: Proceedings of ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games. New York: ACM, 2006. 43–48

    Google Scholar 

  11. Yao J, Wang Y S, Ding B, et al. Facial animation remapping based on spherical parametrization. J Image Graph, 2009, 14: 1406–1412

    Google Scholar 

  12. Chuang E, Bregler C. Performance Driven Facial Animation Using Blendshape Interpolation. Computer Science Technical Report. Stanford University. 2002

    Google Scholar 

  13. Pighin F, Lewis J P. Facial motion retargeting. In: Siggraph 2006 Course Notes: Performance-Driven Facial Animation. New York: ACM, 2006

    Google Scholar 

  14. Blanz V, Vetter A. Morphable model for the synthesis of 3d faces. In: SIGGRAPH′99: Proceedings of the 26th Annual Conference on Computer Graphics and Interactive Techniques. New York: ACM Press/Addison-Wesley Publishing Co., 1999. 187–194

    Chapter  Google Scholar 

  15. Blanz V, Basso C, Poggio T, et al. Reanimating faces in images and video. Comput Graph Forum, 2003, 22: 641–650

    Article  Google Scholar 

  16. Kalberer G A, Gool L V. Realistic face animation for speech. J Visual Comp Animat, 2002, 13: 97–106

    Article  MATH  Google Scholar 

  17. Pandzic I S. Facial motion cloning. Graph Model, 2003, 65: 385–404

    Article  Google Scholar 

  18. Pyun H, Kim Y, Chae W, et al. An example-based approach for facial expression cloning. In: Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation. Switzerland: Eurographics Association Aire-la-Ville, 2003. 167–176

    Google Scholar 

  19. Yano K, Harada K. A facial expression parameterization by elastic surface model. Int J Comput Game Technol, 2009, 2009: doi:10.1155/2009/397938

    Google Scholar 

  20. Li H, Weise T, Pauly M. Example-based facial rigging. ACM Trans Graphic, 2010, 29: 428103

    Google Scholar 

  21. Park S I, Hodgins J K. Capturing and animating skin deformation in human motion. ACM Trans Graphic, 2006, 25: 881–889

    Article  Google Scholar 

  22. Muller M, Heidelberger B, Teschner M, et al. Meshless deformations based on shape matching. ACM Trans Graphic, 2005, 24: 471–478

    Article  Google Scholar 

  23. Guenter B, Grimm C, Wood D, et al. Making faces. In: International Conference on Computer Graphics and Interactive Techniques, ACM SIGGRAPH 2005 Courses. New York: ACM, 2005. 55–66

    Google Scholar 

  24. Wang Y S, Zhuang Y T, Xiao J, et al. A piece-wise learning approach to 3D facial animation. In: Lecture Notes in Computer Science, Advances in Web Based Learning-ICWL 2007. Berlin/Heidelberg: Springer, 2007. 119–184

    Google Scholar 

  25. Zhuang Y T, Pan Y H, Xiao J. A Modern Approach to Intelligent Animation: Theory and Practice. Berlin/Heidelberg: Springer, 2008

    Google Scholar 

  26. Sifakis E, Neverov I, Fedkiw R. Automatic determination of facial muscle activations from sparse MoCap marker data. In: ACM SIGGRAPH 2005. New York: ACM, 2005. 417–425

    Chapter  Google Scholar 

  27. Somasundaram A, Parent R. A facial animation system for expressive audio-visual speech. OSU-CISRC-4/06-TR46. Columbus, OH: Department of Computer Science and Engineering, The Ohio State University, 2006

    Google Scholar 

  28. Joshi P, Tien W C, Desbrun M, et al. Learning controls for blend shape based realistic facial animation. In: Eurographics/SIGGRAPH Symposium on Computer Animation. New York: ACM, 2003

    Google Scholar 

  29. Kyung-Gun N, Moon-Ryul J. Weighted local shape blending for facial motion retargeting. Comp Animat Virt World, 2010, 21: 255–265

    Google Scholar 

  30. Takamizawa R, Suzuki T, Kubo H, et al. Expressive facial subspace construction from key face selection. In: SIGGRAPH 2009. New York: ACM, 2009. 3–7

    Google Scholar 

  31. Pighin F, Hecker J, Lischinski D, et al. Synthesizing realistic facial expressions from photographs. In: Proceedings of SIGGRAPH 98. Computer Graphics Proceedings, Annual Conference Series. New York: ACM, 1998. 75–84

    Google Scholar 

  32. Enciso R, Li J, Fidaleo D, et al. Synthesis of 3D faces. In: International Workshop on Digital and Computational Video. 2000. 8–15

    Google Scholar 

  33. Ulgen F. A step toward universal facial animation via volume morphing. In: 6th IEEE International Workshop on Robot and Human communication. 1997. 358–363

    Google Scholar 

  34. Jin S, Lewis R R, West D. A comparison of algorithms for vertex normal computation. Visual Comput, 2005, 21: 71–82

    Article  Google Scholar 

  35. Botsch M, Kobbelt L. Real-time shape editing using radial basis functions. Eurograph, 2005, 24: 611–621

    Google Scholar 

  36. Fernando R. GPU Gems: Programming Techniques, Tips and Tricks for Real-Time Graphics. America: Pearson Higher Education, 2006. 491–497

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Ministry of Education, Key Laboratory of Advanced Design and Intelligent Computing (Dalian University), Dalian, 116622, China

    XiaoYong Fang, XiaoPeng Wei, Qiang Zhang & ChangJun Zhou

  2. School of Management, Dalian University of Technology, Dalian, 116023, China

    ChangJun Zhou

Authors
  1. XiaoYong Fang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. XiaoPeng Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qiang Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. ChangJun Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to XiaoYong Fang, XiaoPeng Wei or Qiang Zhang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Fang, X., Wei, X., Zhang, Q. et al. On the simulation of expressional animation based on facial MoCap. Sci. China Inf. Sci. 56, 1–12 (2013). https://doi.org/10.1007/s11432-011-4468-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11432-011-4468-4

Keywords

Search

Navigation