3D-3D facial registration method applied to personal identification: Does it work with limited portions of faces? An experiment in ideal conditions.
J Forensic Sci
; 67(4): 1708-1714, 2022 Jul.
Article
em En
| MEDLINE
| ID: mdl-35225363
ABSTRACT
Personal identification of faces represents a challenging issue, especially for what concerns the quantification of the comparison. The 3D-3D superimposition approach proved to distinguish between matches and mismatches. However, the potential of this procedure applied to cases where only parts of faces are visible still has to be verified. This study aimed at verifying the applicability of a 3D-3D procedure to faces divided into three thirds. 3D models of fifty male subjects acquired through stereophotogrammetry were used. The 3D facial models were divided into upper, middle, and lower thirds and registered onto other models belonging to the same and different individuals according to the least point-to-point distance. In total, 50 matches and 50 mismatches were analyzed. RMS value (root mean square) of point-to-point distance between the two facial surfaces was calculated through VAM® software. Statistically significant differences between matches and mismatches in each facial third were assessed through Mann-Whitney test (p < 0.05). On average, RMS value in matches was 0.32 ± 0.12 mm in upper third, 0.36 ± 0.15 mm in middle third, and 0.40 ± 0.20 mm in lower third, respectively; in mismatches, RMS value was 1.40 ± 0.32 mm in upper third, 1.96 ± 0.58 mm in middle third, and 2.39 ± 0.90 mm in lower third, respectively. Differences in RMS values between matches and mismatches were significantly different for all facial thirds, without superimpositions (p < 0.01). This study shows that the existing 3D-3D superimposition methods may be useful also when only a limited portion of face is visible in ideal conditions. Their application to forensic cases of identification still needs to be verified.
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Base de dados:
MEDLINE
Assunto principal:
Fotogrametria
/
Imageamento Tridimensional
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Itália