• DocumentCode
    3664626
  • Title

    Distinguishable de-identified faces

  • Author

    Zongji Sun;Li Meng;Aladdin Ariyaeeinia

  • Author_Institution
    School of Engineering and Technology, University of Hertfordshire, Hatfield, AL10 9AB, UK
  • Volume
    4
  • fYear
    2015
  • fDate
    5/1/2015 12:00:00 AM
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The k-anonymity approach adopted by k-Same face de-identification methods enables these methods to serve their purpose of privacy protection. However, it also forces every k original faces to share the same de-identified face, making it impossible to track individuals in a k-Same de-identified video. To address this issue, this paper presents an approach to the creation of distinguishable de-identified faces. This new approach can serve privacy protection perfectly whilst producing de-identified faces that are as distinguishable as their original faces.
  • Keywords
    "Privacy","Face recognition","Active appearance model","Clustering algorithms","Testing","Brightness","Facial features"
  • Publisher
    ieee
  • Conference_Titel
    Automatic Face and Gesture Recognition (FG), 2015 11th IEEE International Conference and Workshops on
  • Type

    conf

  • DOI
    10.1109/FG.2015.7285019
  • Filename
    7285019