• DocumentCode
    3585863
  • Title

    Metadata-based understanding of impostor pair score variations

  • Author

    Sgroi, Amanda ; Bowyer, Kevin ; Flynn, Patrick

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Univ. of Notre Dame, Notre Dame, IN, USA
  • fYear
    2014
  • Firstpage
    7
  • Lastpage
    12
  • Abstract
    Metadata about a given face image can include information such as the subject´s year of birth, subject gender, and date of acquisition. By determining the degree of metadata matches between the gallery and probe images (such as two subjects having the same gender) we hypothesize that more metadata values that match for an impostor image pair increases the likelihood of a false match. In this work, we explore year of birth, gender, date of acquisition, and expression in an attempt to understand variations in match scores produced by impostor image pairs. Impostor pairs that fall in the weak partition as identified by the previously developed SNoW technique have a slightly larger number of matching metadata values. However, there is little to no statistically significant difference in the scores produced by image pairs with more matching metadata between strong and weak impostor pairs.
  • Keywords
    face recognition; image matching; meta data; SNoW technique; face image; impostor image pair; impostor pair score variation; matching metadata value; metadata matches; metadata-based understanding; probe images; Algorithm design and analysis; Face; Face recognition; Image recognition; Market research; Partitioning algorithms; Snow; biometrics; face recognition; metadata; score analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Forensics and Security (WIFS), 2014 IEEE International Workshop on
  • Type

    conf

  • DOI
    10.1109/WIFS.2014.7084295
  • Filename
    7084295