Skip to main content

AUTOMATIC FACE SYNTHESIS AND ANALYSIS. A QUICK SURVEY

  • Chapter
Computer Vision and Graphics

Part of the book series: Computational Imaging and Vision ((CIVI,volume 32))

Abstract

Considerable interest has been received in automatic face synthesis and analysis over the last three decades. This paper surveys the current state of the art in face synthesis, and also presents face detection and eye detection selected algorithms along with facial feature extraction approach based on using Harris corner detector in face analysis.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

REFERENCES

  1. VIRTUE, EU IST Project IST-1999-10044, http://www.virtue.eu.com

    Google Scholar 

  2. Microsoft NetMeeting, http://www.microsoft.com/windows/netmeeting/

    Google Scholar 

  3. Access Grid, http://www.accessgrid.org

    Google Scholar 

  4. F. Parke and K. Waters, “Computer facial animation”, A K Peters, Ltd, 1996.

    Google Scholar 

  5. ISO/IEC IS 14496-2: MPEG-4 Visual, 1999.

    Google Scholar 

  6. PlayMail, http://playmail.research.att.com

    Google Scholar 

  7. EPTAMEDIA, www.eptamedia.com

    Google Scholar 

  8. G. C. Feng and P. C. Yuen, “Recognition of head-&-shoulder face image using virtual frontal-view image”, IEEE Trans. on Systems, Man, and Cybernetics-Part A: Cybernetics, Vol. 30, No. 6, pp. 871–883, 2000.

    Google Scholar 

  9. S. Valente and J. Dugelay, “A visual analysis/synthesis feedback loop for accurate face tracking”, Signal Processing: Image Communication, Vol. 16, pp. 585–608, 2001.

    Article  Google Scholar 

  10. K. Aizawa and T. S. Huang, “Model-based image coding: advanced video coding techniques for very low bit-rate applications”, Proceedings of the IEEE, Vol. 83, No. 2, pp. 259–271, February 1995.

    Article  Google Scholar 

  11. D. Pearson, “Developments in model-based video coding”, Proceedings of the IEEE, Vol. 83, No. 6, pp. 892–906, June 1995.

    Article  Google Scholar 

  12. F. Parke, “A parametric model for human faces”, Tech. Report UTEC-CSc-75-047, University of Utah, 1974.

    Google Scholar 

  13. K. Waters, “A muscle model for animating three-dimensional facial expression”, Computer Graphics, Vol. 21, No. 4, pp. 17–24, 1987.

    MathSciNet  Google Scholar 

  14. D. Terzopoulos and K. Waters, “Physically-based facial modeling, analysis, and animation”, The Journal of Visualization and Computer Animation, Vol. 1, pp. 73–80, 1990.

    Google Scholar 

  15. Y. Zhang, E. Sung and E. C. Prakash, “A physically-based model for real-time facial expression animation”, Proc. of 3rd Conf. on 3D Digital Imaging and Modeling, pp. 399–406, 2001.

    Google Scholar 

  16. G. C. Feng, P. C. Yuen and J. H. Lai, “Virtual view face image synthesis using 3D spring-based face model from a single image”, 4th Int. conf. on Automatic Face and Gesture Recognition, pp. 530–535, 2000.

    Google Scholar 

  17. CANDIDE, http://www.icg.isy.liu.se/candide

    Google Scholar 

  18. M. Rydfalk, “CANDIDE, a parameterised face”, Report No. LiTH-ISY-I-866, University of Linkoping, Sweden, 1987.

    Google Scholar 

  19. B. Welsh, “Model-based coding of images”, PhD Dissertation, British Telecom Research Lab, Jan. 1991.

    Google Scholar 

  20. J. Ahlberg, “CANDIDE-3: an undated parameterised face”, Report No. LiTH-ISY-R-2326, Linkoping University, Sweden, January 2001.

    Google Scholar 

  21. I.T. Jolliffe, “Principal Component Analysis, Second Edition”, Springer, 2002.

    Google Scholar 

  22. M. Turk, and A. Pentland, “Eigenfaces for Recognition”, Journal of Cognitive Neuroscience, 3(1): 71–86, 1991.

    Google Scholar 

  23. V. Blanz, S. Romdhani and T. Vetter, “Face Identification across Different Poses and Illumination with a 3D Morphable Model”, Proc. FG’02, pp. 202–207, 2002.

    Google Scholar 

  24. CYBERWARE Home Page, http://www.cyberware.com

    Google Scholar 

  25. P. Eisert and Bernd Girod, “Analyzing facial expression for virtual conferencing”, IEEE Trans. on Computer Graphics and Application, Vol. 18, No. 5, pp. 70–78, 1998.

    Google Scholar 

  26. D. Terzopoulos and K. Waters, “Analysis and synthesis of facial image sequences using physical and anatomical models”, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 15, No. 6, pp. 569–579, 1993.

    Article  Google Scholar 

  27. R. Lengagne, J. Tarel and O. Monga, “From 2D images to 3D face geometry”, Proc. of 2nd Int. Conf. on Automatic Face and Gesture Recognition”, pp. 301–306, Oct. 1996.

    Google Scholar 

  28. G. Galicia and A. Zakhor, “Depth based recovery of human facial features from video sequences”, Proc. of IEEE Int. Conf. on Image Processing, Vol. 2, pp. 603–606, 1995.

    Google Scholar 

  29. R. Lengagne, P. Fua, O. Monga, “3D stereo reconstruction of human faces driven by differential constraints”, Image and Vision Computing, Vol. 18, pp. 337–343, 2000.

    Article  Google Scholar 

  30. Z. Zhang, “A flexible new technique for camera calibration”, IEEE Trans. on PAMI, Vol. 22. No. 11. pp. 1330–1334, 2000.

    Google Scholar 

  31. C. Cheng and S. Lai, “An integrated approach to 3D face model reconstruction from video”, IEEE ICCV Workshop on Recognition, Analysis and Tracking of Face and Gestures in Real-Time System, Vancouver, Canada, pp. 16–22, 2001.

    Google Scholar 

  32. Z. Zhang, Z. Liu, D. Adler, M.F. Cohen. R. Hanson and Y. Shan, “Robust and rapid generation of animated faces from video images: a model-based modeling approach”, Microsoft Research, Technique Report, MSR-TR-2001-101, 2001.

    Google Scholar 

  33. Goto, W. Lee, N. Magnenat-Thalmann, “Facial feature extraction for quick 3D face modeling”, Signal Processing: Image Communication 17 (2002) 243–259.

    Article  Google Scholar 

  34. W. Gao, Y. Chen, R. Wang, S. Shan and D. Jiang, “Learning and synthesizing MPEG-4 compatible 3D face animation from video sequence”, IEEE Trans. on Circuit and Systems for Video Technology, Vol. 13, No. 11, pp. 1119–1128, 2003.

    Google Scholar 

  35. W. Lee and N. Magnenat-Thalmann, “Fast head modeling for animation”, Image and Vision Computing 18 (2000) 355–364.

    Article  Google Scholar 

  36. I. Park, H. Zhang, V. Vezhnevets and H. Choh, “Image-based photorealistic 3D face modeling”, Proc. of the 6th International Conference on Automatic Face and Gesture Recognition, 2004.

    Google Scholar 

  37. S. Morishima, “Face analysis and synthesis”, IEEE Signal Processing Magazine, pp. 26–34, May 2001.

    Google Scholar 

  38. T. Vetter and T. Poggio, “Linear object classes and image synthesis from a single example image”, IEEE Trans. on PAMI, Vol. 19, No. 7, pp. 733–742, 1997.

    Google Scholar 

  39. Y. Hu, D. Jiang, S. Yan, L. Zhang, H. Zhang, “Automatic 3D reconstruction for face recognition”, Proc. of the 6th IEEE Int. Conf. on Automatic Face and Gesture Recognition, 2004.

    Google Scholar 

  40. C. Kuo, R. Huang and T. Lin, “3D facial model estimation from single front-view facial image”, IEEE Trans. on CSVT, Vol. 12, No. 3, 2002.

    Google Scholar 

  41. A. Valle, J. Ostermann, “3D talking head customization by adapting a generic model to one uncalibrated picture”, Proc. of IEEE Int. Symposium on Circuits and Systems, Vol. 2, pp. 325–328, 2001.

    Google Scholar 

  42. S. Ho and H. Huang, “Facial modeling from an uncalibrated face image using a coarse-to-fine genetic algorithm”, Patten Recognition 34 (2001) 1015–1031.

    Google Scholar 

  43. P. Viola, M. Jones, “Rapid Object Detection using a Boosted Cascade of Simple Features”, Computer Vision and Pattern Recognition, December 2001.

    Google Scholar 

  44. R. Xiao, M.-J. Li, H.-J. Zhang, “Robust Multipose Face Detection in Images”, IEEE Trans. on Circuits and Systems for Video Technology”, January 2004.

    Google Scholar 

  45. Y. Freund, R.E. Shapire, “A decision theoretic generalization of on-line learning and an application to boosting”, Journal of Computer and Systems Sciences, 55(1):119–139, August 1997.

    Google Scholar 

  46. W. Skarbek, K. Kucharski, “Tutorial on Face and Eye Detection by AdaBoost Method”, special VISNET session at Polish National Conference on Radiocommunications and Broadcasting KKRRiT, 16–18 June, 2004.

    Google Scholar 

  47. A. Pietrowcew, “Face detection and face recognition in digital images”, Ph.D. dissertation in Polish, Warsaw, 2004.

    Google Scholar 

  48. Y. Ma, S. Soatto, J. Kosecka, S. Shankar Sastry, “An Invitation to 3-D Vision. From images to geometric models”, Springer-Verlag, New York, 2004.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer

About this chapter

Cite this chapter

Sheng, Y., Kucharski, K., Sadka, A., Skarbek, W. (2006). AUTOMATIC FACE SYNTHESIS AND ANALYSIS. A QUICK SURVEY. In: Wojciechowski, K., Smolka, B., Palus, H., Kozera, R., Skarbek, W., Noakes, L. (eds) Computer Vision and Graphics. Computational Imaging and Vision, vol 32. Springer, Dordrecht. https://doi.org/10.1007/1-4020-4179-9_22

Download citation

  • DOI: https://doi.org/10.1007/1-4020-4179-9_22

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-4178-5

  • Online ISBN: 978-1-4020-4179-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics