View in EDS PDF Full Text

Preliminary performance assessment of computer automated facial approximations using computed tomography scans of living individuals.

Saved in:
Bibliographic Details
Title: Preliminary performance assessment of computer automated facial approximations using computed tomography scans of living individuals.
Authors: Parks, Connie L.1, Richard, Adam H.1, Monson, Keith L.1 Keith.Monson@ic.fbi.gov
Source: Forensic Science International. 2013, Vol. 233 Issue 1-3, p133-139. 7p.
Subjects: Development of application software, Facial reconstruction (Anthropology), United States. Federal Bureau of Investigation, GE Global Research (Company), Computed tomography, Reface (Company), Forensic anthropology, Resemblance (Philosophy)
Abstract: ReFace (Reality Enhancement Facial Approximation by Computational Estimation) is a computer-automated facial approximation application jointly developed by the Federal Bureau of Investigation and GE Global Research. The application derives a statistically based approximation of a face from a unidentified skull using a dataset of ∼400 human head computer tomography (CT) scans of living adult American individuals from four ancestry groups: African, Asian, European and Hispanic (self-identified). To date only one unpublished subjective recognition study has been conducted using ReFace approximations. It indicated that approximations produced by ReFace were recognized above chance rates (10%). This preliminary study assesses: (i) the recognizability of five ReFace approximations; (ii) the recognizability of CT-derived skin surface replicas of the same individuals whose skulls were used to create the ReFace approximations; and (iii) the relationship between recognition performance and resemblance ratings of target individuals. All five skin surface replicas were recognized at rates statistically significant above chance (22-50%). Four of five ReFace approximations were recognized above chance (5-18%), although with statistical significance only at the higher rate. Such results suggest reconsideration of the usefulness of the type of output format utilized in this study, particularly in regard to facial approximations employed as a means of identifying unknown individuals. [ABSTRACT FROM AUTHOR]
Copyright of Forensic Science International is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Links:
  – Type: pdflink
Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 92766504
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Preliminary performance assessment of computer automated facial approximations using computed tomography scans of living individuals.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Parks%2C+Connie+L%2E%22">Parks, Connie L.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Richard%2C+Adam+H%2E%22">Richard, Adam H.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Monson%2C+Keith+L%2E%22">Monson, Keith L.</searchLink><relatesTo>1</relatesTo><i> Keith.Monson@ic.fbi.gov</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Forensic+Science+International%22">Forensic Science International</searchLink>. 2013, Vol. 233 Issue 1-3, p133-139. 7p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Development+of+application+software%22">Development of application software</searchLink><br /><searchLink fieldCode="DE" term="%22Facial+reconstruction+%28Anthropology%29%22">Facial reconstruction (Anthropology)</searchLink><br /><searchLink fieldCode="DE" term="%22United+States%2E+Federal+Bureau+of+Investigation%22">United States. Federal Bureau of Investigation</searchLink><br /><searchLink fieldCode="DE" term="%22GE+Global+Research+%28Company%29%22">GE Global Research (Company)</searchLink><br /><searchLink fieldCode="DE" term="%22Computed+tomography%22">Computed tomography</searchLink><br /><searchLink fieldCode="DE" term="%22Reface+%28Company%29%22">Reface (Company)</searchLink><br /><searchLink fieldCode="DE" term="%22Forensic+anthropology%22">Forensic anthropology</searchLink><br /><searchLink fieldCode="DE" term="%22Resemblance+%28Philosophy%29%22">Resemblance (Philosophy)</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: ReFace (Reality Enhancement Facial Approximation by Computational Estimation) is a computer-automated facial approximation application jointly developed by the Federal Bureau of Investigation and GE Global Research. The application derives a statistically based approximation of a face from a unidentified skull using a dataset of ∼400 human head computer tomography (CT) scans of living adult American individuals from four ancestry groups: African, Asian, European and Hispanic (self-identified). To date only one unpublished subjective recognition study has been conducted using ReFace approximations. It indicated that approximations produced by ReFace were recognized above chance rates (10%). This preliminary study assesses: (i) the recognizability of five ReFace approximations; (ii) the recognizability of CT-derived skin surface replicas of the same individuals whose skulls were used to create the ReFace approximations; and (iii) the relationship between recognition performance and resemblance ratings of target individuals. All five skin surface replicas were recognized at rates statistically significant above chance (22-50%). Four of five ReFace approximations were recognized above chance (5-18%), although with statistical significance only at the higher rate. Such results suggest reconsideration of the usefulness of the type of output format utilized in this study, particularly in regard to facial approximations employed as a means of identifying unknown individuals. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Forensic Science International is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=92766504
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.forsciint.2013.08.031
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 7
        StartPage: 133
    Subjects:
      – SubjectFull: Development of application software
        Type: general
      – SubjectFull: Facial reconstruction (Anthropology)
        Type: general
      – SubjectFull: United States. Federal Bureau of Investigation
        Type: general
      – SubjectFull: GE Global Research (Company)
        Type: general
      – SubjectFull: Computed tomography
        Type: general
      – SubjectFull: Reface (Company)
        Type: general
      – SubjectFull: Forensic anthropology
        Type: general
      – SubjectFull: Resemblance (Philosophy)
        Type: general
    Titles:
      – TitleFull: Preliminary performance assessment of computer automated facial approximations using computed tomography scans of living individuals.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Parks, Connie L.
      – PersonEntity:
          Name:
            NameFull: Richard, Adam H.
      – PersonEntity:
          Name:
            NameFull: Monson, Keith L.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 10
              Text: 2013
              Type: published
              Y: 2013
          Identifiers:
            – Type: issn-print
              Value: 03790738
          Numbering:
            – Type: volume
              Value: 233
            – Type: issue
              Value: 1-3
          Titles:
            – TitleFull: Forensic Science International
              Type: main
ResultId 1