A Biometric Interface to Ambient Intelligence Environments

  • Andrea F. Abate
  • Michele Nappi
  • Stefano Ricciardi
Conference paper


As domotic technologies are evolving from home automation towards Ambient Intelligence, context aware adaptive solutions for advanced environment management are emerging, featuring a broad range of services customized on each user’s specific needs. This scenario offers the opportunity to exploit the potential of face as a not intrusive biometric identifier not only to regulate access to the controlled environment but to adapt the ambient intelligence to the preferences of the recognized user. In this paper we present a 3D face recognition method applied to such an Ambient Intelligence framework. The proposed approach relies on stereoscopic face acquisition and 3D mesh reconstruction to avoid highly expensive and not automated 3D scanners, typically not suited for real time applications. For each subject enrolled, a bi-dimensional feature descriptor is extracted from its 3D mesh and compared to the previously stored correspondent template. This descriptor is a normal map, namely a color image in which RGB components represent the normals to the face geometry. A weighting mask, automatically generated for each authorized person, improves recognition robustness to a wide range of facial expression.


Face Recognition Iterative Close Point Ambient Intelligence Iterative Close Point Face Recognition System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    E. Aarts and S. Marzano, eds., “The New Everyday: Visions of Ambient Intelligence”, 010 Publishing, Rotterdam, The Netherlands, 2003.Google Scholar
  2. 2.
    D. Maltoni, D. Maio, A.K. Jain, S. Prabhakar, “Handbook of Fingerprint Recognition”, Springer, New York, 2003Google Scholar
  3. 3.
    G. Perronnin, J.L. Dugelay, “An Introduction to biometrics and face recognition”, in Proc. of IMAGE 2003: Learning, Understanding, Information Retrieval, Medical, Cagliari, Italy, June 2003.Google Scholar
  4. 4.
    M. S. Bartlett, J. R. Movellan and T. J. Sejnowski, “Face Recognition by Independent Component Analysis”, in IEEE Transactions on Neural networks, vol. 13, no. 6, pp. 1450–1464, November 2002.CrossRefGoogle Scholar
  5. 5.
    J. Zhang, Y. Yan and M. Lades, “Face Recognition: Eigenface, Elastic Matching, and Neural Nets” in Proc. of the IEEE, vol. 85, no. 9, pp. 1423–1435, September 1997.CrossRefGoogle Scholar
  6. 6.
    T. Tan, H. Yan, “Face recognition by fractal transformations”, in Proc. of 1999 IEEE Int. Conference on Acoustics, Speech, and Signal Processing, vol. 6, no. 6, pp. 3537–3540, March 1999.Google Scholar
  7. 7.
    P. J. Phillips, P. Grother, R. J. Micheals, D. M. Blackburn, E. Tabassi, M. Bone, “Face Recognition Vendor Test: Evaluation Report”,, March 2003.
  8. 8.
    B. Achermann, X. Jiang, and H. Bunke, “Face recognition using range images”, in Proc. of International Conference on Virtual Systems and MultiMedia, pp. 129–136, 1997.Google Scholar
  9. 9.
    B. Achermann and H. Bunke, “Classifying range images of human faces with the hausdorff distance”, in Proc. of 15th International Conference on Pattern Recognition, Barcelona, Spain, pp. 2: 813–817, 2000.Google Scholar
  10. 10.
    H. T. Tanaka, M. Ikeda, and H. Chiaki, “Curvature-based face surface recognition using spherical correlation principal directions for curved object recognition”, in Proc. of Third International Conference on Automated Face and Gesture Recognition, pp. 372–377, 1998.Google Scholar
  11. 11.
    C. Hesher, A. Srivastava, and G. Erlebacher, “A novel technique for face recognition using range images”, in Proc. of Seventh Int’l Symp. on Signal Processing and Its Applications, Paris, France, Jul. 2003.Google Scholar
  12. 12.
    G. Medioni and R. Waupotitsch. Face recognition and modeling in 3D. in Proc. of IEEE Int’l Workshop on Analysis and Modeling of Faces and Gestures (AMFG 2003), pp. 232–233, October 2003.Google Scholar
  13. 13.
    X. Gu, S. Gortler and H. Hoppe, “Geometry images”, in Proc. of SIGGRAPH 2002, San Antonio, Texas, ACM, pp. 355–361, Jul. 2002.Google Scholar
  14. 14.
    G. Acampora, E. Loia, M. Nappi, S. Ricciardi, “Ambient Intelligence Framework for context aware adaptive applications”, in IEEE Proc. of CAMP2005 Conference, Palermo, Italy, July 2005.Google Scholar
  15. 15.
    R. Enciso, J. Li, D.A. Fidaleo, T-Y Kim, J-Y Noh and U. Neumann, “Synthesis of 3D Faces”, in Proc. of International Workshop on Digital and Computational Video (DCV’99), December 1999.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Andrea F. Abate
    • 1
  • Michele Nappi
    • 1
  • Stefano Ricciardi
    • 1
  1. 1.University of SalernoFiscianoItaly

Personalised recommendations