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from the false-positives-are-a-bad-thing-said-one-of-the-twins dept.
If you've watched any sort of spy thriller or action film over the last few years – think Jason Bourne or Mission: Impossible – the chances are you've seen facial recognition software in action. These movie scenes often involve an artist's sketch compared to mug shots, or sometimes even a live CCTV stream, and with the clock ticking, a match is usually found for the culprit in the nick of time.
It seems natural then to assume that what happens in the film world is similar to what happens (most of the time) in the real world. We might think that our faces are constantly being tracked and recognised as we walk past security cameras in city centres – but this is not actually the case.
Not only would such a system require millions of cameras capable of producing high-quality footage, but it would also require the integration of photo-ID databases such as mugshots from every police force, previous passport images, and driving license images for everyone in the country.
And yet even if this high level of integration was possible, a far more basic problem still exists – facial recognition systems are still not 100% accurate.
(Score: 2) by pe1rxq on Friday December 16 2016, @04:24PM
The trick is not to compare against millions each time.
When you see someone on a camera you only have to be able to compare to the cameras next to it.
This way you can track people with a much higher probability and together with other clues (like the cell tower a phone is connected to) you can get close to 100% certainty.