Literature DB >> 21431334

Can facial proportions taken from images be of use for ageing in cases of suspected child pornography? A pilot study.

Cristina Cattaneo1, Zuzana Obertová, Melanie Ratnayake, Laura Marasciuolo, J Tutkuviene, Pasquale Poppa, Daniele Gibelli, Peter Gabriel, S Ritz-Timme.   

Abstract

The age of the victim plays a crucial role for the legal implications concerning pornography. Judges therefore often call on forensic experts to verify the age of individuals depicted on photographs or videos. However, there is no scientifically established protocol available for forensic practice in such cases. The conventional methods such as the evaluation of secondary sexual characteristics provide unsatisfactory results particularly when the legally relevant ages for child pornography (i.e. 14 and 18 years) are concerned. To overcome these limits, a European research group has explored the applicability of facial proportions as an age indicator on images. In this pilot study, standardized facial images of 353 females and 20 males from four age groups (6, 10, 14 and 18 years) were randomly selected for the metric analysis from a large data set including German, Italian and Lithuanian subjects. In this sample, several indices extracted from the frontal and lateral photographs were closely correlated to their respective indices taken from the living individuals. Furthermore, age-related changes were identified for indices taken from the photographs. The discriminant analysis showed that for the pooled sample, 60.3% of the cases were correctly classified into the respective age group. The percentage of correctly classified cases increased in the respective country samples as follows: 69.9% for Germany, 69.4% for Lithuania and 80.5% for Italy. The present study suggests that the metric assessment of the face may be used for age estimation on images. Nonetheless, more work needs to be done in order to verify the reliability of these findings on a large sample.

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Year:  2011        PMID: 21431334     DOI: 10.1007/s00414-011-0564-7

Source DB:  PubMed          Journal:  Int J Legal Med        ISSN: 0937-9827            Impact factor:   2.686


  19 in total

1.  Tanner staging and pornography.

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Journal:  Pediatrics       Date:  1999-10       Impact factor: 7.124

Review 2.  Age estimation: the state of the art in relation to the specific demands of forensic practise.

Authors:  S Ritz-Timme; C Cattaneo; M J Collins; E R Waite; H W Schütz; H J Kaatsch; H I Borrman
Journal:  Int J Legal Med       Date:  2000       Impact factor: 2.686

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Authors:  Carol D Berkowitz
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Authors:  Shumei S Sun; Christine M Schubert; William Cameron Chumlea; Alex F Roche; Howard E Kulin; Peter A Lee; John H Himes; Alan S Ryan
Journal:  Pediatrics       Date:  2002-11       Impact factor: 7.124

5.  Variations in pattern of pubertal changes in girls.

Authors:  W A Marshall; J M Tanner
Journal:  Arch Dis Child       Date:  1969-06       Impact factor: 3.791

6.  A craniofacial growth maturity gradient for males and females between 4 and 16 years of age.

Authors:  P H Buschang; R M Baume; G G Nass
Journal:  Am J Phys Anthropol       Date:  1983-07       Impact factor: 2.868

7.  Accuracy of pubertal Tanner staging self-reporting.

Authors:  Jean-Claude Desmangles; Joan M Lappe; Gina Lipaczewski; Gleb Haynatzki
Journal:  J Pediatr Endocrinol Metab       Date:  2006-03       Impact factor: 1.634

Review 8.  [Problems associated with chronological age estimation of children exploited in child pornography production].

Authors:  Jarosław Bednarek
Journal:  Arch Med Sadowej Kryminol       Date:  2006 Jul-Sep

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Authors:  V F Ferrario; C Sforza; C E Poggio; J H Schmitz
Journal:  Plast Reconstr Surg       Date:  1999-03       Impact factor: 4.730

Review 10.  Age estimation of unaccompanied minors. Part I. General considerations.

Authors:  A Schmeling; W Reisinger; G Geserick; A Olze
Journal:  Forensic Sci Int       Date:  2006-03-09       Impact factor: 2.395

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  7 in total

1.  The juvenile face as a suitable age indicator in child pornography cases: a pilot study on the reliability of automated and visual estimation approaches.

Authors:  M Ratnayake; Z Obertová; M Dose; P Gabriel; H M Bröker; M Brauckmann; A Barkus; R Rizgeliene; J Tutkuviene; S Ritz-Timme; L Marasciuolo; D Gibelli; C Cattaneo
Journal:  Int J Legal Med       Date:  2013-06-02       Impact factor: 2.686

2.  Pitfalls at the root of facial assessment on photographs: a quantitative study of accuracy in positioning facial landmarks.

Authors:  M Cummaudo; M Guerzoni; L Marasciuolo; D Gibelli; A Cigada; Z Obertovà; M Ratnayake; P Poppa; P Gabriel; S Ritz-Timme; C Cattaneo
Journal:  Int J Legal Med       Date:  2013-03-21       Impact factor: 2.686

3.  Age estimation based on pictures and videos presumably showing child or youth pornography.

Authors:  F Mayer; T Arent; G Geserick; C Grundmann; U Lockemann; T Riepert; A Schmeling; St Ritz-Timme
Journal:  Int J Legal Med       Date:  2014-05-18       Impact factor: 2.686

4.  Estimating a child's age from an image using whole body proportions.

Authors:  Teghan Lucas; Maciej Henneberg
Journal:  Int J Legal Med       Date:  2017-02-23       Impact factor: 2.686

5.  A new approach for the analysis of facial growth and age estimation: Iris ratio.

Authors:  Carlos Eduardo Palhares Machado; Marta Regina Pinheiro Flores; Laíse Nascimento Correia Lima; Rachel Lima Ribeiro Tinoco; Ademir Franco; Ana Cristina Barreto Bezerra; Martin Paul Evison; Marco Aurélio Guimarães
Journal:  PLoS One       Date:  2017-07-07       Impact factor: 3.240

6.  Simulation of facial growth based on longitudinal data: Age progression and age regression between 7 and 17 years of age using 3D surface data.

Authors:  Jana Koudelová; Eva Hoffmannová; Ján Dupej; Jana Velemínská
Journal:  PLoS One       Date:  2019-02-22       Impact factor: 3.240

7.  The age distribution of facial metrics in two large Korean populations.

Authors:  Hae-Young Lee; Seongwon Cha; Hyo-Jeong Ban; In-Young Kim; Bo-Reum Park; Ig-Jae Kim; Kyung-Won Hong
Journal:  Sci Rep       Date:  2019-10-10       Impact factor: 4.379

  7 in total

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