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Related Experiment Videos

Use of Facial Recognition Software to Identify Disaster Victims With Facial Injuries.

John Broach1, Rothsovann Yong2, Mary-Elise Manuell3

  • 11University of Massachusetts Medical School/University of Massachusetts Memorial Medical Center,Worcester,Massachusetts.

Disaster Medicine and Public Health Preparedness
|April 11, 2017
PubMed
Summary
This summary is machine-generated.

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Facial recognition software can aid disaster victim identification, correctly matching injured individuals 39-45% of the time. Optimal photo quality significantly increases accuracy, exceeding 90% in many cases.

Area of Science:

  • Disaster Medicine
  • Forensic Science
  • Biometrics

Background:

  • Victim identification is critical after large-scale disasters for family reunification and proper disposition.
  • Current methods for identifying disaster victims with facial trauma can be challenging.

Purpose of the Study:

  • To evaluate the effectiveness of commercially available facial recognition software in identifying disaster victims with simulated facial injuries.

Main Methods:

  • 106 participants had pre- and post-moulage photos taken to simulate facial injuries.
  • Facial recognition software analyzed these images alongside personal photo collections.
  • The software's accuracy in identifying individuals with simulated facial trauma was assessed.

Main Results:

Keywords:
disaster medicinedisaster victim identificationfacial recognitionmass casualty incidents

Related Experiment Videos

  • Facial recognition software achieved correct match rates between 39% and 45% for injured disaster victim photos.
  • Accuracy significantly improved to over 90% when submitted photos were of optimal quality.
  • The software demonstrated potential utility despite lower accuracy with injured facial images.

Conclusions:

  • Commercial facial recognition software can offer substantial benefits to disaster responders.
  • Even with a 40% accuracy rate, the technology can assist in identifying large numbers of victims.
  • Further research may refine software performance for disaster victim identification.