Passive 3D Face Reconstruction with 3D Digital Image Correlation

Conference paper
First Online:
Part of the Conference Proceedings of the Society for Experimental Mechanics Series book series (CPSEMS)

Abstract

Digital Image Correlation (DIC) is a widely used technique in the optics and mechanics fields for shape and deformation measurements. However, it is normally not used to measure the 3D shapes of human faces because of the requirement of speckle-pattern fabrication. In this paper, we demonstrate that the 3D DIC can be employed to reconstruct 3D images of human faces without using active speckle patterns either projected or fabricated on the faces. The technique involves a combination of the 3D DIC algorithm and the scale-invariant feature transform (SIFT) algorithm.

Keywords

Digital image correlation Passive face reconstruction Subset size Calculation step size Step size 
This is a preview of subscription content, log in to check access.

References

  1. 1.
    Garcia E, Dugelay J-L (2001) Low cost 3D face acquisition and modeling. In: International conference on information technology: coding and computing, Las Vegas, NV, pp 657–661Google Scholar
  2. 2.
    Bradley D, Heidrich W, Popa T, Sheffer A (2010) High resolution passive facial performance capture. In: ACM transaction on graphics (Proceedings of SIGGRAPH). ACM, New York, p 41Google Scholar
  3. 3.
    Hossain MS, Akbar M, Starkey JD (2013) Inexpensive construction of a 3D face model from stereo images. In: The third international conference on communications and information technology (ICCIT)Google Scholar
  4. 4.
    Zhang L, Snavely N, Curless B, Seitz SM (2004) Spacetimefaces: high resolution capture for modeling and animation. In: ACM transaction on graphics (Proceedings of SIGGRAPH), pp 548–558Google Scholar
  5. 5.
    Wang Y, Huang X, Lee C-S, Zhang S, Li Z, Samaras D, Metaxas D, Elgammal A, Huang P (2004) High resolution acquisition, learning and transfer of dynamic 3-D facial expressions. In: Computer graphics forum, pp 677–686Google Scholar
  6. 6.
    Furukawa Y, Ponce J (2009) Dense 3D motion capture for human faces. In: 2009 IEEE conference on computer vision and pattern recognitionGoogle Scholar
  7. 7.
    Bickel B, Botsch M, Angst R, Matusik W, Otaduy M, Pfister H, Gross M (2007) Multi-scale capture of facial geometry and motion. In: ACM transaction on graphics (Proceedings of SIGGRAPH), New York, p 33Google Scholar
  8. 8.
    Ma W-C, Jones A, Chiang J-Y, Hawkins T, Frederiksen S, Peers P, Vukovic M, Ouhyoung M, Debevec B (2008) Facial performance synthesis using deformation-driven polynomial displacement maps. ACM Trans Graph (Proc SIGGRAPH Asia) 27(5):121Google Scholar
  9. 9.
    Pan B, Xie H, Yang L, Wang Z (2009) Accurate measurement of satellite antenna surface using 3D digital image correlation technique. Strain 45(2):194–200CrossRefGoogle Scholar
  10. 10.
    Vo M, Wang Z, Luu L, Ma J (2011) Advanced geometric camera calibration for machine vision. Opt Eng 50:110503CrossRefGoogle Scholar
  11. 11.
    Wang Z, Vo M, Kieu H, Pan T (2014) Automated fast initial guess in digital image correlation. Strain 50(1):28–36CrossRefGoogle Scholar
  12. 12.
    Lowe D (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60:91–110CrossRefGoogle Scholar
  13. 13.
    Muja M, Lowe DG (2009) Fast approximate nearest neighbors with automatic algorithm configuration. In: VISAPP international conference on computer vision theory and applicationsGoogle Scholar
  14. 14.
    Pan B, Qian K, Xie H, Asundi A (2009) Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review. Meas Sci Technol 20:062001CrossRefGoogle Scholar
  15. 15.
    Pan B, Xie H, Wang Z (2010) Equivalence of digital image correlation criteria for pattern matching. Appl Opt 49:5501–5509CrossRefGoogle Scholar
  16. 16.
    Lourakis MIA, Argyros AA (2005) Is Levenberg-Marquardt the most efficient optimization algorithm for implementing bundle adjustment? In: tenth IEEE international conference on computer vision (ICCV), p 2Google Scholar
  17. 17.
    Luu L, Wang Z, Vo M, Hoang T, Ma J (2010) Accuracy enhancement of digital image correlation with B-spline interpolation. Opt Lett 36(16):3070–3072CrossRefGoogle Scholar
  18. 18.
    Kieu H, Pan T, Wang Z, Le M, Nguyen H, Vo M (2014) Accurate 3D shape measurement of multiple separate objects with stereo vision. Meas Sci Technol 25(3), 035401CrossRefGoogle Scholar
  19. 19.
    Wang Z, Hoang T, Nguyen D, Urcinas A, Magro J (2010) High-speed digital image correlation method: comment. Opt Lett 35(17):2891CrossRefGoogle Scholar
  20. 20.
    Hu Z, Xie H, Lu J, Wang H, Zhu J (2011) Error evaluation technique for three-dimensional digital image correlation. Appl Opt 50:6239–6247CrossRefGoogle Scholar
  21. 21.
    Vo M, Wang Z, Pan B, Pan T (2012) Hyper-accurate flexible calibration technique for fringe-projection-based three-dimensional imaging. Opt Express 20(15):16926–16941CrossRefGoogle Scholar

Copyright information

© The Society for Experimental Mechanics, Inc. 2015

Authors and Affiliations

  • Hien Kieu
    • 1
  • Zhaoyang Wang
    • 2
  • Minh Le
    • 1
  • Hieu Nguyen
    • 1
  1. 1.Department of Electrical EngineeringThe Catholic University of AmericaWashington, DCUSA
  2. 2.Department of Mechanical EngineeringThe Catholic University of AmericaWashington, DCUSA

Personalised recommendations