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Application of the Self-Organizing Feature Map Algorithm in Facial Image Morphing

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Abstract

A new facial image morphing algorithm based on the Kohonen self-organizing feature map (SOM) algorithm is proposed to generate a smooth 2D transformation that reflects anchor point correspondences. Using only a 2D face image and a small number of anchor points, we show that the proposed morphing algorithm provides a powerful mechanism for processing facial expressions.

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References

  1. Nishita, T. and Nakamae, E.: Metamorphosis using Bezier Clipping, Proceeding of the 1st Pacific Conference in Computer Graphics and Application, Korea (1993), pp. 62–173.

  2. Wolberg, G.: Digital Image Warping, IEEE Computer Society Press, 1990.

  3. Beier, T and Neely, S.: Feature based image metamorphosis, SIGRPH'92 (1992), pp. 25–42.

  4. Raprecht, D. and Muller, H.: Deformed cross-dissolves for image interpolation in scientific visualization, J. Visualization and Computer Animation, 5(3) (1994), 167–181.

    Google Scholar 

  5. Arad, N., Dyn, N., and Reisfeld, D.: Image warping by radial basis functions: Application to facial expressions, Computer Vision, Graphics and Image Processing, 56(3) (1994), 161–172.

    Google Scholar 

  6. Arad, N. and Reisfeld, C.: Image warping using few anchor points and radial functions, Computer Graphics Forum, 14(1) (1995), 35–46.

    Google Scholar 

  7. Bookstein, F. L.: Principal warps: Thin plate splines and the decomposition of deformations, IEEE Transactions on Pattern Analysis Machine Intelligence, 11(6) (1989), 567–585.

    Google Scholar 

  8. Aboul-Ella, H. and Nakajima, M.: Image morphing of facial images transformation based on navier elastic body splines, Computer Animation 98. Proceedings (1998), pp. 119–125.

  9. Goshtasby, A.: Piecewise linear mapping functions for image registration, Pattern Recognition, 20(5) (1987), 525–533.

    Article  Google Scholar 

  10. Kohonen, T., Oja, E., Simula, O., Visa, A. and Kangas, J.: Engineering application of the self-organizing map, Proceedings of the IEEE, 84(10) (1996), 1358–1383.

    Google Scholar 

  11. Kohonen, T.: Self-Organization and Associate Memory, Springer-Verlag, London, 1984.

    Google Scholar 

  12. Waters, K.: A muscle model for animating three-dimensional facial expression, Computer Graphics ACMSIGGRAPH, 24(4) (1987), 17–24.

    Google Scholar 

  13. Terzopoulos, D. and Waters, K.: Physically based facial modeling, analysis and animation, Visualization and Computer Animation, 1(2) (1990), 73–80.

    Google Scholar 

  14. Platt, S. M. and Badler, N. I.: Animating facial expressions, Computer Graphics, 15(3) (1981), 245–252.

    Google Scholar 

  15. Ekman, P. and Friesen, W. V.: Manual for the Facial Action Coding system, Consulting Pyschologists Press, Im., Palo Alto, CA, 1978.

    Google Scholar 

  16. Kalra, P., Mangili, A., Thalmann, N. M., and Thalmann, D.: Simulation of Facial Muscle Actions Based on Rational Free Form Deformations, Eurographics, 11(3) (1992), 59–69.

    Google Scholar 

  17. Magnenat-Thalmann, N., Primeau, N. E., and Thalmann D.: Abstract muscle actions procedures for human face animation, Visual Computer, 3(5) (1988), 290–297.

    Google Scholar 

  18. Essa, I. and Pentland, A.: Facial expression recognition using a dynamic model and motion energy, Proc. of Int. Conf. on Computer Vision, Los Alamitos, CA (1995), pp. 360–367.

  19. Parke, F. I.: Computer Generated Animation of Faces, Master's Thesis, 1972, University of Utah.

  20. Parke, F. I.: Parameterized models for facial animation, IEEE Computer Graphics and Applications, 2(9) (1982), 61–68.

    Google Scholar 

  21. Parke, F. I. and Waters, K.: Computer Facial Animation, A. K. Peters, 1996.

  22. Bulthoff, H. H. and Edelman, S.: Psychophysical support for a 2D view interpolation theory of object recognition, Proc. Natl. Acad. Sci., 89 (1992), 60–64.

    Google Scholar 

  23. Dyn, N.: Interpolation and approximation by radial and related function. In: Approximation Theory VI, C. K. Chui, L. L. Schumaker, and J. D. Ward (eds), Academic Press, San Diego, 1 (1989), 211–234.

    Google Scholar 

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Su, MC., Liu, IC. Application of the Self-Organizing Feature Map Algorithm in Facial Image Morphing. Neural Processing Letters 14, 35–47 (2001). https://doi.org/10.1023/A:1011378024388

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