• DocumentCode
    2722471
  • Title

    Combination of user- and enrollee-specific statistical information in verification systems

  • Author

    Cheng, Xi ; Tulyakov, Sergey ; Govindaraju, Venu

  • Author_Institution
    Center for Unified Biometrics & Sensors, Univ. at Buffalo, Buffalo, NY, USA
  • fYear
    2011
  • fDate
    20-25 June 2011
  • Firstpage
    126
  • Lastpage
    131
  • Abstract
    Instead of using matching scores between single enrolled and single test (or user) template, the matching scores related to all test templates or all enrolled ones can be considered to enhance the performance of biometric systems. The user-specific methods take into account the dependencies of matching scores assigned to different enrollees being matched to one test template. On the other hand, enrolled template specific methods consider the relationship among matching scores between different user inputs and one enrolled template. In this paper, we consider the combination of user and enrollee specific statistical information by utilizing various statistical models. The experiments show that the combination of user and enrollee specific methods can further improve the performance of both unimodal and multimodal biometric systems compared to solely using either user or enrollee specific models.
  • Keywords
    biometrics (access control); image matching; statistical analysis; enrolled template specific methods; enrollee specific statistical information; matching scores; multimodal biometric system; unimodal biometric system; user specific statistical information; verification system; Biological system modeling; Biometrics; Correlation; Databases; Face; Kernel; NIST;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition Workshops (CVPRW), 2011 IEEE Computer Society Conference on
  • Conference_Location
    Colorado Springs, CO
  • ISSN
    2160-7508
  • Print_ISBN
    978-1-4577-0529-8
  • Type

    conf

  • DOI
    10.1109/CVPRW.2011.5981837
  • Filename
    5981837