Advertisement

Enhancing 3D Face Recognition by a Robust Version of ICP Based on the Three Polar Representation

  • Amal RihaniEmail author
  • Majdi JribiEmail author
  • Faouzi GhorbelEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 684)

Abstract

In this paper, we intend to propose a framework for the description and the matching of three dimensional faces. Our starting point is the representation of the 3D face by an invariant description under the M(3) group of translations and rotations. This representation is materialized by the points of the arc-length reparametrization of all the level curves of the three polar representation. These points are indexed by their level curve number and their position in each level. With this type of description we need a step of registration to align 3D faces with different expressions. Therefore, we propose to use a robust version of the iterative closest point algorithm (ICP) adopted to 3D face recognition context. We test the accuracy of our approach on a part of the BU-3DFE database of 3D faces. The obtained results for many protocols of the identification scenario show the performance of such framework.

Keywords

3D face Description Three polar representation The arc-length reparametrization Registration Haussdorff ICP BU-3DFE 

References

  1. 1.
    Paquet E., Rioux M.: A query by content system for three-dimensional model and image databases management. In: The 17th conference on Image and Vision Computing, pp. 157–166 (1999)Google Scholar
  2. 2.
    Osada, R., Funkhouser, T., Chazelle, B., Dobkin, D.: Shape distributions. ACM Trans. Graph. 21(4), 807–832 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
  3. 3.
    Shinagawa, Y., Kunii, T.-L., Kergosien, Y.-L.: Surface coding based on morse theory. IEEE Comput. Graph. 11, 66–78 (1991)CrossRefGoogle Scholar
  4. 4.
    Ganguly, S., Bhattacharjee, D., Nasipuri, M.: 3D face recognition from range images based on curvature analysis. ICTACT J. Image Video Process. 4(3), 748 (2014)CrossRefGoogle Scholar
  5. 5.
    Samir, C., Srivastava, A., Daoudi, M.: Three dimensional face recognition using shapes of facial curves. IEEE Trans. Pattern Anal. Mach. Intell. 28(11), 1858–1863 (2006)CrossRefGoogle Scholar
  6. 6.
    Srivastava, A., Samir, C., Joshi, S.H., Daoudi, M.: Elastic shape models for face anlysis using curvilinear coordinates. J. Math. Imaging Vision 33(2), 253–265 (2008)CrossRefGoogle Scholar
  7. 7.
    Gadacha, W., Ghorbel, F.: A new 3D surface registration approach depending on a suited resolution: application to 3D faces. In: IEEE Mediterranean and Electrotechnical Conference (MELECON), Hammamet, Tunisia (2012)Google Scholar
  8. 8.
    Ghorbel, F., Jribi, M.: A robust invariant bipolar representation for R3 surfaces: applied to the face description: Springer. Ann. Telecommun. 68(3–4), 219–230 (2013)CrossRefGoogle Scholar
  9. 9.
    Jribi, M., Ghorbel, F.: A stable and invariant three-polar surface representation: application to 3D face description. In: WSCG 2014, the 22nd International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, Republic (2014)Google Scholar
  10. 10.
    Ghorbel, F.: A unitary formulation for invariant image description: application to image coding 53(5–6), 242–260 (1998). Special issue Annales des telecommunicationsGoogle Scholar
  11. 11.
    Ghorbel, F.: Invariants for shapes and movement. Eleven cases from 1D to 4D and from Euclidean to Projectives (French version), Arts-pi edn., Tunisia (2012)Google Scholar
  12. 12.
    Besl, P.J., Mckay, N.D.: A method for registration of 3-D shapes. IEEE Trans. Pattern Anal. Mach. Intell. 14(2), 239–256 (1992)CrossRefGoogle Scholar
  13. 13.
    Sethian, J.A.: A fast marching level set method for monotonically advancing fronts. Proc. Nat. Acad. Sci. 93, 1591–1595 (1996)MathSciNetCrossRefzbMATHGoogle Scholar
  14. 14.
    Rihani, A., Jribi, M., Ghorbel, F.: A novel accurate 3D surfaces description using the arc-length reparametrized level curves of the three-polar representation. In: WSCG 2016, the 24th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, Republic (2016)Google Scholar
  15. 15.
    Ayache, N.: Computer vision applied to 3D medical imagery: results, trends and future challenges. In: Proceedings of the 6th Symposium on Robotics Research. MIT Press, also Inria Tech. (1993)Google Scholar
  16. 16.
    Faugeras, O., Hebert, M.: The representation, recognition and positioning of 3d shapes from range data. In: Proceedings of the 8th International Conference On Artificial Intelligence, Karlsruhe, BRD, pp. 996–1002, August 1983Google Scholar
  17. 17.
    Rigoutsos, I., Hummel, R.: Robust similarity invariant matching in the presence of noise: a data parallel approach. In: Proceedings of the 8th Israeli Conference on Artificial Intelligence and Computer VisionGoogle Scholar
  18. 18.
    Gueziec, A., Ayache, N.: Smoothing and matching of 3D-space curves. In: Proceedings of the Second Europeen Conference on Computer Vision Santa Maragherita Ligure, Italy, May 1992Google Scholar
  19. 19.
    Bannour, M.T., Ghorbel, F.: Isotropie de la représentation des surfaces; Application à la description et la visualisation d’objets 3D. In: RFIA 2000, pp. 275–282 (2000)Google Scholar
  20. 20.
    Lijun, Y., Xiaozhou, W., Yi, S., Jun, W., Matthew, J.: A 3D facial expression database for facial behavior research. In: The 7th International Conference on Automatic Face and Gesture Recognition, pp. 211–216 (2006)Google Scholar
  21. 21.
    Szeptycki, P., Ardabilian, M., Chen, L.: A coarse-to-fine curvature analysis-based rotation invariant 3D face landmarking, In: The IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems, BTAS 2009 (2009)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.CRISTAL Laboratory, GRIFT Research Group, National School of Computer ScienceUniversity of ManoubaLa ManoubaTunisia

Personalised recommendations