De-Duplication Using Automated Face Recognition: A Mathematical Model and All Babies Are Equally Cute

Luuk Spreeuwers*

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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    Abstract

    De-duplication is defined as the technique to eliminate or link duplicate copies of repeating data. We consider a specific de-duplication application where a subject applies for a new passport and we want to check if he possesses a passport already under another name. To determine this, a facial photograph of the subject is compared to all photographs of the national database of passports. We investigate if state of the art facial recognition is up to this task and find that for a large database about 2 out of 3 duplicates can be found while few or no false duplicates are reported. This means that de-duplication using automated face recognition is feasible in practice. We also present a mathematical model to predict the performance of de-duplication and find that the probability that k false duplicates are returned can be described well by a Poisson distribution using a varying, subject specific false match rate. We present experimental results using a large database of actual passport photographs consisting of 224 000 images of about 100 000 subjects and find that the results are predicted well by our model.

    Original languageEnglish
    Title of host publication2017 International Conference of the Biometrics Special Interest Group, BIOSIG 2017
    PublisherGesellschaft für Informatik
    ISBN (Electronic)978-3-88579-664-0
    ISBN (Print)978-1-5386-0396-3
    DOIs
    Publication statusPublished - 28 Sep 2017
    Event16th International Conference of the Biometrics Special Interest Group 2017 - Darmstadt, Germany
    Duration: 20 Sep 201722 Sep 2017
    Conference number: 16
    http://fg-biosig.gi.de/archiv/biosig-2017.html

    Conference

    Conference16th International Conference of the Biometrics Special Interest Group 2017
    Abbreviated titleBIOSIG 2017
    CountryGermany
    CityDarmstadt
    Period20/09/1722/09/17
    Internet address

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