Face recognition is increasingly being used in access control for primary or secondary authentication, giving users an automated, frictionless experience. Access cards are easy to duplicate and to lose, leaving offices and secure facilities at greater risk of unwanted intrusion. But you always carry your face with you, and anti-spoofing technology makes sure it’s yours. Today’s multi-core camera chips allow you to embed face recognition software in the camera itself, so you don’t even need a server.
Race and gender bias in face recognition can be an issue if the recognition models have been built with insufficiently diverse datasets. Often, the datasets are biased towards the gender and race of the developers themselves, who tend to be white males. But there are datasets available with millions of faces of all races and both genders. At IntelliVision we have ensured that our facial recognition models have been built and tested with multiple ethnicities and genders, ensuring that everyone can be detected.
Adding face recognition to turnstiles and gates can improve both security and speed, leading to a frictionless experience for staff or for people passing through checkpoints. Image databases can be created from existing employee records or passport data.
But what about “spoofing”, where someone holds up a photograph or even a cellphone video of the person’s face? Won’t that allow the wrong person through? That’s where “anti-spoofing” comes in. Normally this requires a 3D or stereo camera to detect depth and movement. But at IntelliVision we have implemented anti-spoofing in regular 2D cameras, by detecting “liveness” over a number of successive frames. This ensures that only real faces are detected and recognized.