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Danilo De Angelis1, Remo Sala, Angela Cantatore

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Summary
This summary is machine-generated.

This study introduces a novel method for facial identification using 3D facial models compared against 2D surveillance images. This technique aids forensic experts in analyzing facial trait compatibility for suspect identification.

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Area of Science:

  • Forensic Science
  • Computer Vision
  • Biometrics

Background:

  • Facial identification from surveillance footage is challenging due to variations in image quality and pose.
  • Existing methods often struggle with accurate comparison between 2D images and 3D facial data.

Purpose of the Study:

  • To develop and evaluate a procedure for identifying individuals by comparing 3D facial models with 2D surveillance images.
  • To create a tool for analyzing facial trait compatibility between suspects and perpetrators.

Main Methods:

  • Reconstruction of a 3D facial model from suspect scans.
  • Automatic resizing and manual repositioning/reorientation of the 3D model using anthropometric landmarks.
  • Superimposition of the 3D model onto 2D crime scene images for expert analysis.

Main Results:

  • The procedure allows for the superimposition of 3D facial models onto 2D images.
  • Expert judgment is based on the fit between anatomical facial districts.
  • The method effectively reduces the influence of face orientation on identification.

Conclusions:

  • The described procedure offers a valuable tool for facial identification in forensic investigations.
  • Comparing 3D facial models with 2D surveillance data enhances identification accuracy.
  • This technique aids in determining the compatibility of facial traits between suspects and crime scene images.