Literature DB >> 28063586

Juvenile age estimation from facial images.

Eilidh Ferguson1, Caroline Wilkinson2.   

Abstract

Age determination from images can be of vital importance, particularly in cases involving suspected child sexual abuse (CSA). It is imperative to determine if an individual depicted in such an image is indeed a child, with a more concise age often sought, as this may affect the severity of offender sentencing. The aims of this study were to establish the accuracy of visual age estimation of the juvenile face in children aged between 0 and 16years and to determine if varying levels of exposure to children affected an individual's ability to assess age from the face. An online questionnaire consisting of 30 juvenile face images was created using SurveyMonkey®. The overall results suggested poor accuracy for visual age estimation of juvenile faces. The age, sex, occupation and number of children of the participants did not affect the ability to estimate age from facial images. Similarly, the sex and age of the juvenile faces did not appear to affect the accuracy of age estimation. When specific age groups are considered, sex may have an influence on age estimation, with female faces being aged more accurately in the younger age groups and male faces more accurate after the age of 11years, however this is based on a small sample. This study suggests that the accuracy of juvenile age estimation from the face alone is poor using simple visual assessment of images. Further research is required to determine exactly how age is assessed from a facial image, if there are indicators, or features in particular that lead to over- or under-estimation of juvenile age.
Copyright © 2016 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Age estimation; Child pornography; Face; Image; Juvenile

Mesh:

Year:  2016        PMID: 28063586     DOI: 10.1016/j.scijus.2016.08.005

Source DB:  PubMed          Journal:  Sci Justice        ISSN: 1355-0306            Impact factor:   2.124


  3 in total

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Authors:  Sandeep Kumar Gupta; Neeta Nain
Journal:  Multimed Tools Appl       Date:  2022-06-15       Impact factor: 2.577

2.  Two sources of bias explain errors in facial age estimation.

Authors:  Colin W G Clifford; Tamara L Watson; David White
Journal:  R Soc Open Sci       Date:  2018-10-17       Impact factor: 2.963

Review 3.  Real-Time Gender Recognition for Juvenile and Adult Faces.

Authors:  Sandeep Kumar Gupta; Seid Hassen Yesuf; Neeta Nain
Journal:  Comput Intell Neurosci       Date:  2022-03-17
  3 in total

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