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Low Cost Virtual Face Performance Capture Using Stereo Web Cameras

  • Alexander Woodward
  • Patrice Delmas
  • Georgy Gimel’farb
  • Jorge Marquez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4872)

Abstract

A complete system for creating the performance of a virtual character is described. Stereo web-cameras perform marker based motion capture to obtain rigid head motion and non-rigid facial expression motion. Acquired 3D points are then mapped onto a 3D face model with a virtual muscle animation to create face expressions. Muscle inverse kinematics updates muscle contraction parameters based on marker motion to create the character’s performance. Advantages of the system are reduced character creation time by using virtual muscles and a dynamic skin model, a novel way of applying markers to a face animation system, and its low cost hardware requirements, capable of running on standard hardware and making it suitable for interactive media in end-user environments.

Keywords

Computer Vision Web-camera Markers Motion capture Facial animation Virtual character 

References

  1. 1.
    Autodesk. 3ds max (2007), http://www.autodesk.com/3dsmax
  2. 2.
    Autodesk. Autodesk maya (2007), http://www.autodesk.com/maya
  3. 3.
    Barton, G., Delmas, P.: A semi-automated colour predicate for robust skin detection. In: Proc. Image and Vision Computing New Zealand, pp. 121–125 (2002)Google Scholar
  4. 4.
    Baxter, B.: Fast numerical methods for inverse kinematics (2007), http://billbaxter.com/courses/290/html/index.htm
  5. 5.
    Neverov, I., Sifakis, E., Fedkiw, R.: Automatic determination of facial muscle activations from sparse motion capture marker data. In: ACM Transactions on Graphics (SIGGRAPH Proceedings), pp. 417–425. ACM Press, New York (2005)Google Scholar
  6. 6.
    Ekman, P., Friesen, W.V.: Constants across cultures in the face and emotion. Journal of Social and Personality Psychology, 124–129 (1971)Google Scholar
  7. 7.
    famous3D. famous3D (2007), http://famous3d.com/
  8. 8.
    Montgomery, J., Borshukov, G., Hable, J.: GPU Gems 3 - Playable Universal Capture, ch. 15, pp. 485–504. Addison-Wesley Professional, Reading (2007)Google Scholar
  9. 9.
    Cherrie, J., Mitchell, T., Fright, W., McCallum, B., Carr, J., Beatson, R., Evans, T.: Reconstruction and representation of 3D objects with radial basis functions. In: ACM SIGGRAPH, pp. 67–76. ACM Press, New York (2001)Google Scholar
  10. 10.
    Xiao, J., Chai, J., Hodgins, J.: Vision-based control of 3d facial animation. In: Proc. of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation, ACM Press, New York (2003)Google Scholar
  11. 11.
    Curless, B., Zhang, L., Snavely, N., Seitz, S.: Spacetime faces: High-resolution capture for modeling and animation. In: ACM Annual Conference on Computer Graphics, pp. 548–558. ACM Press, New York (2004)Google Scholar
  12. 12.
    Mova. Mova (2007), http://www.mova.com/
  13. 13.
    Noh, J., Neumann, U.: A survey of facial modeling and animation techniques. In: USC Technical Report, University of Southern California (1993)Google Scholar
  14. 14.
    Paterson, J., Fitzgibbon, A.: 3D head tracking using non-linear optimization. In: Proc. of the British Machine Vision Conference 2003, vol. 2, pp. 609–618 (2003)Google Scholar
  15. 15.
    HomePage of Applied Research Associates NZ Ltd (ARANZ): Interpolating scattered data with RBFs (2007), http://www.aranz.com/research/modelling/theory/rbffaq.html
  16. 16.
    Softimage. Face robot (2007), http://www.softimage.com/products/facerobot/
  17. 17.
    Motek Motion Technology. Motek - motion technology (2007), http://www.e-motek.com/
  18. 18.
    Tsai, R.Y.: A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses. IEEE Journal of Robotics and Automation, 323–344 (1987)Google Scholar
  19. 19.
    Unibrain. Unibrain fire-i digital camera (2007), http://www.unibrain.com/Products/VisionImg/Fire_i_DC.htm
  20. 20.
    Vicon. Vicon (2007), http://www.vicon.com/
  21. 21.
    Welman, C.: Inverse kinematics and geometric constraints for articulated figure manipulation. Master thesis, Simon Fraser University (1993)Google Scholar
  22. 22.
    Woodward, A., Delmas, P.: Towards a low cost realistic human face modelling and animation framework. Proc. Image and Vision Computing New Zealand, 11–16 (2004)Google Scholar
  23. 23.
    Woodward, A., Delmas, P.: Computer vision for low cost 3-D golf ball and club tracking. Proc. Image and Vision Computing New Zealand (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Alexander Woodward
    • 1
  • Patrice Delmas
    • 1
  • Georgy Gimel’farb
    • 1
  • Jorge Marquez
    • 2
  1. 1.Department of Computer Science, The University of Auckland, AucklandNew Zealand
  2. 2.Image Analysis Visualization Laboratory, CCADET UNAMMexico

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