Forensic Face Recognition: A Survey

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

    6 Citations (Scopus)
    145 Downloads (Pure)

    Abstract

    The improvements of automatic face recognition during the last 2 decades have disclosed new applications like border control and camera surveillance. A new application field is forensic face recognition. Traditionally, face recognition by human experts has been used in forensics, but now there is a quickly developing interest in automatic face recognition as well. At the same time there is a trend towards a more objective and quantitative approach for traditional manual face comparison by human experts. Unlike in most applications of face recognition, in the forensic domain a binary decision or a score does not suffice as a result to be used in court. Rather, in the forensic domain, the outcome of the recognition process should be in the form of evidence or support for a prosecution hypothesis verses a defence hypothesis. In addition, in the forensic domain, trace images are often of poor quality. The available literature on (automatic) forensic face recognition is still very limited. In this survey, an overview is given of the characteristics of forensic face recognition and the main publications. The survey introduces forensic face recognition and reports on attempts to use automatic face recognition in the forensic context. Forensic facial comparison by human experts and the development of guidelines and a more quantitative and objective approach are also addressed. Probably the most important topic of the survey is the development of a framework to use automatic face recognition in the forensic setting. The Bayesian framework is a logical choice and likelihood ratios can in principle be used directly in court. In the statistical evaluation of the trace image, the choice of databases of facial images plays a very important role.
    Original languageUndefined
    Title of host publicationFace Recognition: Methods, Applications and Technology
    EditorsAdamo Quaglia, Calogera M. Epifano
    PublisherNOVA Publishers
    Pages9
    Number of pages19
    ISBN (Print)978-1-61942-663-4
    Publication statusPublished - 2012

    Publication series

    NameComputer Science, Technology and Applications
    PublisherNova Publishers

    Keywords

    • METIS-285109
    • Bayesian framework
    • IR-79599
    • SCS-Safety
    • Forensics
    • EWI-21465
    • Face Recognition

    Cite this

    Ali, T., Spreeuwers, L. J., & Veldhuis, R. N. J. (2012). Forensic Face Recognition: A Survey. In A. Quaglia, & C. M. Epifano (Eds.), Face Recognition: Methods, Applications and Technology (pp. 9). (Computer Science, Technology and Applications). NOVA Publishers.
    Ali, Tauseef ; Spreeuwers, Lieuwe Jan ; Veldhuis, Raymond N.J. / Forensic Face Recognition: A Survey. Face Recognition: Methods, Applications and Technology. editor / Adamo Quaglia ; Calogera M. Epifano. NOVA Publishers, 2012. pp. 9 (Computer Science, Technology and Applications).
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    title = "Forensic Face Recognition: A Survey",
    abstract = "The improvements of automatic face recognition during the last 2 decades have disclosed new applications like border control and camera surveillance. A new application field is forensic face recognition. Traditionally, face recognition by human experts has been used in forensics, but now there is a quickly developing interest in automatic face recognition as well. At the same time there is a trend towards a more objective and quantitative approach for traditional manual face comparison by human experts. Unlike in most applications of face recognition, in the forensic domain a binary decision or a score does not suffice as a result to be used in court. Rather, in the forensic domain, the outcome of the recognition process should be in the form of evidence or support for a prosecution hypothesis verses a defence hypothesis. In addition, in the forensic domain, trace images are often of poor quality. The available literature on (automatic) forensic face recognition is still very limited. In this survey, an overview is given of the characteristics of forensic face recognition and the main publications. The survey introduces forensic face recognition and reports on attempts to use automatic face recognition in the forensic context. Forensic facial comparison by human experts and the development of guidelines and a more quantitative and objective approach are also addressed. Probably the most important topic of the survey is the development of a framework to use automatic face recognition in the forensic setting. The Bayesian framework is a logical choice and likelihood ratios can in principle be used directly in court. In the statistical evaluation of the trace image, the choice of databases of facial images plays a very important role.",
    keywords = "METIS-285109, Bayesian framework, IR-79599, SCS-Safety, Forensics, EWI-21465, Face Recognition",
    author = "Tauseef Ali and Spreeuwers, {Lieuwe Jan} and Veldhuis, {Raymond N.J.}",
    year = "2012",
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    series = "Computer Science, Technology and Applications",
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    booktitle = "Face Recognition: Methods, Applications and Technology",

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    Ali, T, Spreeuwers, LJ & Veldhuis, RNJ 2012, Forensic Face Recognition: A Survey. in A Quaglia & CM Epifano (eds), Face Recognition: Methods, Applications and Technology. Computer Science, Technology and Applications, NOVA Publishers, pp. 9.

    Forensic Face Recognition: A Survey. / Ali, Tauseef; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

    Face Recognition: Methods, Applications and Technology. ed. / Adamo Quaglia; Calogera M. Epifano. NOVA Publishers, 2012. p. 9 (Computer Science, Technology and Applications).

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

    TY - CHAP

    T1 - Forensic Face Recognition: A Survey

    AU - Ali, Tauseef

    AU - Spreeuwers, Lieuwe Jan

    AU - Veldhuis, Raymond N.J.

    PY - 2012

    Y1 - 2012

    N2 - The improvements of automatic face recognition during the last 2 decades have disclosed new applications like border control and camera surveillance. A new application field is forensic face recognition. Traditionally, face recognition by human experts has been used in forensics, but now there is a quickly developing interest in automatic face recognition as well. At the same time there is a trend towards a more objective and quantitative approach for traditional manual face comparison by human experts. Unlike in most applications of face recognition, in the forensic domain a binary decision or a score does not suffice as a result to be used in court. Rather, in the forensic domain, the outcome of the recognition process should be in the form of evidence or support for a prosecution hypothesis verses a defence hypothesis. In addition, in the forensic domain, trace images are often of poor quality. The available literature on (automatic) forensic face recognition is still very limited. In this survey, an overview is given of the characteristics of forensic face recognition and the main publications. The survey introduces forensic face recognition and reports on attempts to use automatic face recognition in the forensic context. Forensic facial comparison by human experts and the development of guidelines and a more quantitative and objective approach are also addressed. Probably the most important topic of the survey is the development of a framework to use automatic face recognition in the forensic setting. The Bayesian framework is a logical choice and likelihood ratios can in principle be used directly in court. In the statistical evaluation of the trace image, the choice of databases of facial images plays a very important role.

    AB - The improvements of automatic face recognition during the last 2 decades have disclosed new applications like border control and camera surveillance. A new application field is forensic face recognition. Traditionally, face recognition by human experts has been used in forensics, but now there is a quickly developing interest in automatic face recognition as well. At the same time there is a trend towards a more objective and quantitative approach for traditional manual face comparison by human experts. Unlike in most applications of face recognition, in the forensic domain a binary decision or a score does not suffice as a result to be used in court. Rather, in the forensic domain, the outcome of the recognition process should be in the form of evidence or support for a prosecution hypothesis verses a defence hypothesis. In addition, in the forensic domain, trace images are often of poor quality. The available literature on (automatic) forensic face recognition is still very limited. In this survey, an overview is given of the characteristics of forensic face recognition and the main publications. The survey introduces forensic face recognition and reports on attempts to use automatic face recognition in the forensic context. Forensic facial comparison by human experts and the development of guidelines and a more quantitative and objective approach are also addressed. Probably the most important topic of the survey is the development of a framework to use automatic face recognition in the forensic setting. The Bayesian framework is a logical choice and likelihood ratios can in principle be used directly in court. In the statistical evaluation of the trace image, the choice of databases of facial images plays a very important role.

    KW - METIS-285109

    KW - Bayesian framework

    KW - IR-79599

    KW - SCS-Safety

    KW - Forensics

    KW - EWI-21465

    KW - Face Recognition

    M3 - Chapter

    SN - 978-1-61942-663-4

    T3 - Computer Science, Technology and Applications

    SP - 9

    BT - Face Recognition: Methods, Applications and Technology

    A2 - Quaglia, Adamo

    A2 - Epifano, Calogera M.

    PB - NOVA Publishers

    ER -

    Ali T, Spreeuwers LJ, Veldhuis RNJ. Forensic Face Recognition: A Survey. In Quaglia A, Epifano CM, editors, Face Recognition: Methods, Applications and Technology. NOVA Publishers. 2012. p. 9. (Computer Science, Technology and Applications).