The age progression technique: Study and evaluation of the results

Age progression technique involves a reworking of the photo of a missing person in accordance with the guidelines drawn up by medical sciences on aging. Here we present the age progression of photos of individuals who are not missing persons, so the photos of their current appearance are available. The creation of age progressions in blind starting from photos of them as children made it possible to evaluate the effectiveness of the technique. The age progression was carried out based on a photo of Individual A and Individual B. First, the study of the facial features defined the morphology according to the standard classification, then reference images characterized by morphologies consistent with those of the original image were searched for. Thanks to Adobe Photoshop 2023 software, the creation of a collage was made. Finally, the result was compared with the current photo of the individual. The analysis of the two age progressions carried out gave different results. In the age progression of Individual A, the morphology of the facial features reveals similarities with slight errors in the comparison with his photo at 19 years old. Regarding the age progression of Individual B's face, doubts were raised regarding both skin tone and haircut. The positive and negative aspects found in these age progressions are of great importance in evaluating the accuracy of the results. Thanks to continuous practice, the age progression technique can be improved so that it can be a real support tool for the search for long-time missing persons.

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Publication Details

Journal
Legal Medicine
Published
2025-03-16
DOI
https://doi.org/10.1016/j.legalmed.2025.102611
Citations
3
Primary Topic
3D Shape Modeling and Analysis
Type
article
Field-Weighted Citation Impact
4.00
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article

The age progression technique: Study and evaluation of the results

Laura Donato, Douglas H. Ubelaker, Anna Laura Santunione, Rossana Cecchi et al.
3 citations
Legal Medicine
3D Shape Modeling and Analysis
4.00
article

The age progression technique: Study and evaluation of the results

Laura Donato, Douglas H. Ubelaker, Anna Laura Santunione, Rossana Cecchi, Michele Treglia, Jessika Camatti, Luigi Tonino Marsella, Mark Davis
article en
3 citations

Abstract

Age progression technique involves a reworking of the photo of a missing person in accordance with the guidelines drawn up by medical sciences on aging. Here we present the age progression of photos of individuals who are not missing persons, so the photos of their current appearance are available. The creation of age progressions in blind starting from photos of them as children made it possible to evaluate the effectiveness of the technique. The age progression was carried out based on a photo of Individual A and Individual B. First, the study of the facial features defined the morphology according to the standard classification, then reference images characterized by morphologies consistent with those of the original image were searched for. Thanks to Adobe Photoshop 2023 software, the creation of a collage was made. Finally, the result was compared with the current photo of the individual. The analysis of the two age progressions carried out gave different results. In the age progression of Individual A, the morphology of the facial features reveals similarities with slight errors in the comparison with his photo at 19 years old. Regarding the age progression of Individual B's face, doubts were raised regarding both skin tone and haircut. The positive and negative aspects found in these age progressions are of great importance in evaluating the accuracy of the results. Thanks to continuous practice, the age progression technique can be improved so that it can be a real support tool for the search for long-time missing persons.

Legal MedicineVol. 74
University of Rome Tor Vergata (IT), University of Modena and Reggio Emilia (IT), University of Parma (IT), National Museum of Natural History (US), Office of the Medical Examiner of Cook County (US)
Openalex Percentile: Top 8%
3D Shape Modeling and Analysis
4.00
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