Facial recognition is increasingly used as way to access your money and your devices.
When it comes to policing, it could soon mean the difference between freedom and imprisonment.
Faces can be scanned at a distance, generating a code as unique as your fingerprints.
This is created by measuring the distance between various points, like the width of a person’s nose, distance between the eyes and length of the jawline.
Facial recognition systems check more than 80 points of comparison, known as ‘nodal points’, combining them to build a person’s faceprint.
These faceprints can then be used to search through a database, matching a suspect to known offenders.
Facial recognition is increasingly used as way to access your money and your devices. When it comes to policing, it could soon mean the difference between freedom and imprisonment (stock)
Facial scanning systems used on personal electronic devices function slightly differently, and vary from gadget to gadget.
The iPhone X, for example, uses Face ID via a 7MP front-facing camera on the handset which has multiple components.
One of these is a Dot Projector that projects more than 30,000 invisible dots onto your face to map its structure.
The dot map is then read by an infrared camera and the structure of your face is relayed to the A11 Bionic chip in the iPhone X, where it is turned into a mathematical model.
The A11 chip then compares your facial structure to the facial scan stored in the iPhone X during the setup process.
Security cameras use artificial intelligence powered systems that can scan for faces, re-orient, skew and stretch them, before converting them to black-and-white to make facial features easier for computer algorithms to recognise.
Error rates with facial recognition can be as low as 0.8 per cent. While this sounds low, in the real world that means eight in every 1,000 scans could falsely identify an innocent party..
One such case, reported in The Intercept, details how Steven Talley was falsely matched to security footage of a bank robber.