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Consistent parameterization and statistical analysis of human head scans

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Abstract

Statistical shape analysis of 3-D scanned human heads provides important information for many applications. Nevertheless, special geometry processing techniques have to be developed for consistently parameterizing scans due to the fact that different scanning projects vary in landmark definition, noise control and other factors. For consistent parameterization, fitting a generic model to each scan has proved to be an effective method. In this paper, improved techniques are presented to solve problems in parameterizing different data sets. Principal Component Analysis (PCA) is thus conducted on the consistently parameterized data sets, and shape variances along principal components are demonstrated. In addition, shape variations analyzed by Independent Component Analysis (ICA) are also presented.

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References

  1. Robinette, K., Daanen, H., Paquet, E.: The CAESAR project: A 3-D surface anthropometry survey. In: Proc. 2nd International Conference on 3D Digital Imaging and Modeling (3DIM’99), pp. 380–386 (1999)

  2. Dryden, I.L., Mardia, K.V.: Statistical Shape Analysis. Wiley, New York (1998)

    MATH  Google Scholar 

  3. Bookstein, F.L.: Morphometric Tools for Landmark Data: Geometry and Biology. Cambridge University Press, Cambridge (1997)

    Google Scholar 

  4. Hammond, P., Hutton, T., Allanson, J., Campbell, L., Hennekam, R., Holden, S., Patton, M., Shaw, A., Temple, I.K., Trotter, M., Murphy, K., Winter, R.: 3D analysis of facial morphology. Am. J. Med. Genet. 126A, 339–348 (2004)

    Article  Google Scholar 

  5. Hutton, T., Buxton, B., Hammond, P., Potts, H.: Estimating average growth trajectories in shape-space using kernel smoothing. IEEE Trans. Med. Imaging 22(6), 747–753 (2003)

    Article  Google Scholar 

  6. Dekker, L., Douros, I., Buxton, B.F., Treleaven, P.: Building symbolic information for 3D human body modeling from range data. In: Proceedings of the Second International Conference on 3-D Digital Imaging and Modeling (3DIM’99), Ottawa, Canada, pp. 388–397 (1999)

  7. Ben Azour, Z., Shu, C., Mantel, A.: Automatic locating of anthropometric landmarks on 3D human models. In: Third International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT 2006), pp. 750–757 (2006)

  8. Russ, T., Boehnen, C., Peters, T.: 3D face recognition using 3D alignment for PCA. In: Computer Vision and Pattern Recognition (CVPR’06), pp. 1391–1398 (2006)

  9. DeCarlo, D., Metaxos, D., Stone, M.: An anthropometric face model using variational techniques. In: ACM SIGGRAPH Computer Graphics Proceedings, pp. 67–74 (1998)

  10. Blanz, V., Vetter, T.: A morphable model for the synthesis of 3D faces. In: ACM SIGGRAPH Computer Graphics Proceedings, pp. 187–194 (1999)

  11. Allen, B., Curless, B., Popović, Z.: The space of human body shapes: reconstruction and parameterization from range scans. ACM Trans. Graph. 22(3), 587–594 (2003)

    Article  Google Scholar 

  12. Marschner, S.R., Guenter, B., Raghupathy, S.: Modeling and rendering for realistic facial animation. In: Proceedings of 11th Eurographics Workshop on Rendering, pp. 231–242 (2000)

  13. Xi, P., Lee, W.-S., Shu, C.: Analysis of segmented human body scans. In: Proceedings of the Graphics Interface Conference, pp. 19–26 (2007)

  14. Cohen-Or, D., Solomovic, A., Levin, D.: Three-dimensional distance field metamorphosis. ACM Trans. Graph. 17(2), 116–141 (1998)

    Article  Google Scholar 

  15. Noh, J.Y., Neumann, U.: Expression cloning. In: Proceedings of SIGGRAPH, pp. 277–288 (2001)

  16. Bartlett, M., Movellan, J.R., Sejnowski, T.J.: Face recognition by independent component analysis. IEEE Trans. Neural Netw. 13(6), 1450–1464 (2002)

    Article  Google Scholar 

  17. Kalberer, G.A., Mueller, P., Gool, L.V.: Speech animation using viseme space. In: Proceedings of the Vision, Modeling, and Visualization, pp. 463–470 (2002)

  18. Ruto, A., Lee, M., Buxton, B.: Comparing principal and independent modes of variation in 3-D human torso shape using PCA and ICA. In: Proceedings of ICA Research Network International Workshop, University of Liverpool, pp. 101–104 (2006)

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Authors and Affiliations

  1. Institute for Information Technology, National Research Council Canada, Ottawa, Canada

    Pengcheng Xi & Chang Shu

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  1. Pengcheng Xi
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  2. Chang Shu
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Correspondence to Pengcheng Xi.

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Xi, P., Shu, C. Consistent parameterization and statistical analysis of human head scans. Vis Comput 25, 863–871 (2009). https://doi.org/10.1007/s00371-009-0316-6

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  • DOI: https://doi.org/10.1007/s00371-009-0316-6

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