Forensic Facial Identification using the Fringe P3 brain wave response (EEG-FIT)

Lead Participant: Visionmetric Limited


"The production of facial composites of criminal suspects from eyewitness testimony (commonly known as PhotoFITs or EFITs) is a staple tool used to assist criminal investigations throughout the world. This project proposes a radical, new way of obtaining such images with increased accuracy and speed.

At present, eyewitnesses to crime produce composite images under the guidance of a trained police operator and the process generally involves extensive verbal interaction. The process is thus demanding on human resources (taking 1 - 4 hours) and accuracy is quite low.

The project partners Visionmetric and Prof Howard Bowman, University of Kent aim to overcome the limitations of current methods by combining their expertise and making the necessary advances. The central idea is to present eyewitnesses to a crime a rapid sequence of computer-generated images calculated to resemble the suspect. EEG (electroencephalography) is used to capture an enhanced brain wave response that is observed in response to stimuli which bear resemblance to the criminal offender. This method (known as the fringe P3 method) has been extensively developed by Bowman at University of Kent. Visionmetric specialise in machine learning and AI methods applied to the human face. They propose to develop fast and robust iterative processes for generating increasingly relevant facial images from the P3 signal stream and presenting these to the witness.

This approach is very fast. It directly exploits the normal brainwave activity of the eyewitness and avoids the need for extensive interaction between the witness and operator. The aim will be to show that more accurate images of a suspect can be produced and in a small fraction of the time that is required using existing methods."

Lead Participant

Project Cost

Grant Offer

Visionmetric Limited, LEWES £309,760 £ 216,832


University of Kent, United Kingdom £92,225 £ 92,225


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