Database Cross Matching: A Novel Source of Fictitious Forensic Cases

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    Abstract

    Due to privacy concern and data protection laws, it is very difficult to obtain real forensic data for forensic face recognition research. In this paper, we introduce the concept of Database Cross Matching (DCM) as a novel source of fictitious but challenging forensic cases. DCM refers to the task of finding the subjects that are common in two different data sets. For most pairs of independent data sets, there will be no common subjects. However, for some data sets captured at the same institution, but independently and at different times, there is a high probability of finding some common subjects. We demonstrate the feasibility of DCM using the PIE and MultiPIE data set that were captured at the same institution in 2000 and 2004 respectively. We denote the task of finding the subjects that are common in PIE and MultiPIE data as PIE $\cap$ MultiPIE problem. Evaluation of the five face recognition systems applied to the PIE $\cap$ MultiPIE problem show that DCM can indeed create very challenging forensic problems.
    Original languageUndefined
    Place of PublicationEnschede
    PublisherCentre for Telematics and Information Technology (CTIT)
    Number of pages9
    Publication statusPublished - Sep 2012

    Publication series

    NameCTIT Technical Report Series
    PublisherCentre for Telematics and Information Technology, University of Twente
    No.TR-CTIT-12-23
    ISSN (Print)1381-3625

    Keywords

    • forensic face recognition
    • SCS-Safety
    • METIS-289697
    • IR-84357
    • EWI-22268
    • PIE $\cap$ MultiPIE problem
    • fictitious forensic case
    • PIE MultiPIE problem

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