Tag Detection for Preventing Unauthorized Face Image Processing

  • Alberto Escalada Jimenez
  • Adrian Dabrowski
  • Noburu Sonehara
  • Juan M. Montero Martinez
  • Isao Echizen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9023)


A new technology is being proposed as a solution to the problem of unintentional facial detection and recognition in pictures in which the individuals appearing want to express their privacy preferences, through the use of different tags. The existing methods for face de-identification were mostly ad hoc solutions that only provided an absolute binary solution in a privacy context such as pixelation, or a bar mask. As the number and users of social networks are increasing, our preferences regarding our privacy may become more complex, leaving these absolute binary solutions as something obsolete. The proposed technology overcomes this problem by embedding information in a tag which will be placed close to the face without being disruptive. Through a decoding method the tag will provide the preferences that will be applied to the images in further stages.


Privacy Face detection Tag detection Unauthorized face processing 



This work was performed under the National Institute of Informatics international internship program.


  1. 1.
    Yang, M.-H., Kriegman, D., Ahuja, N.: Detecting faces in images: A survey. IEEE Trans. Pattern Anal. Mach. Intell. 24(1), 34–58 (2002)Google Scholar
  2. 2.
    Zhang, C., Zhang, Z.: A survey of recent advances in face detection, Technical report, Microsoft Research (2010)Google Scholar
  3. 3.
    Sadeghi, A.-R., Schneider, T., Wehrenberg, I.: Efficient privacy-preserving face recognition. In: Lee, D., Hong, S. (eds.) ICISC 2009. LNCS, vol. 5984, pp. 229–244. Springer, Heidelberg (2010) CrossRefGoogle Scholar
  4. 4.
    Bowyer, K.W.: Face recognition technology: security versus privacy. IEEE Technol. Soc. Mag. 23(1), 9–19 (2004)Google Scholar
  5. 5.
    A focus on efficiency,, Techical report (2013)Google Scholar
  6. 6.
    Besmer, A., Lipford, H.R.: Moving beyond untagging: photo privacy in a tagged world. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, pp. 1563–1572 (2010)Google Scholar
  7. 7.
  8. 8.
    How does facebook suggest tags?, May 2014.
  9. 9.
    Dabrowski, A., Weippl, E., Echizen, I.: Framework based on privacy policy hiding for preventing unauthorized face image processing. In: 2013 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 455–461, October 2013Google Scholar
  10. 10.
    Gross, R., Airoldi, E.M., Malin, B., Sweeney, L.: Integrating utility into face de-identification. In: Danezis, G., Martin, D. (eds.) PET 2005. LNCS, vol. 3856, pp. 227–242. Springer, Heidelberg (2006) CrossRefGoogle Scholar
  11. 11.
    M. Corporation. Microsoft tag - implementation guide (2011).
  12. 12.
    How does instagram develop their filters?, May 2012.
  13. 13.
    Viola, P., Jones, M.J.: Robust real-time face detection. Int. J. Comput. Vis. 57(2), 137–154 (2004)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Alberto Escalada Jimenez
    • 1
  • Adrian Dabrowski
    • 2
  • Noburu Sonehara
    • 3
  • Juan M. Montero Martinez
    • 1
  • Isao Echizen
    • 3
  1. 1.E.T.S. Ing. TelecomunicacinUniversidad Politcnica de MadridMadridSpain
  2. 2.SBA ResearchUniversity of TechnologyViennaAustria
  3. 3.National Institue of InformaticsTokyoJapan

Personalised recommendations