Media Reporting on Facial Recognition
Facial recognition has received a lot of bad publicity recently and media reports have highlighted concerns over the invasion of privacy and the constant monitoring of our daily lives.
Privacy advocates have deemed the technology ‘unlawful’, ‘dangerously inaccurate’, and claim ‘fail rates of 92%’. These reports are extremely misleading, but headlines of this nature tend to resonate and as such, there is a broadly negative perception of facial recognition with the public.
These reports are mainly based on previous evaluations of the technology going back a few years. False match figures reported to be 90% and above are largely taken out of context and highlight misunderstandings on how test data has been presented and therefore are not a reflection of its true accuracy.
However, the technology has now reached a level of maturity and accuracy allowing it to be deployed and integrated across a wide range of critical applications and sectors. In fact, there are vendors who can verify accuracy rates of 98% and above with false match rates (based on a 1:1 comparison) of 1 in a billion.
Facial Recognition and Optimisation of CCTV
Advancing
Facial Recognition Technology The Facts
F
acial recognition is a hot topic and there
has been considerable media interest in the development and use of this technology. Many companies are banking on it as a technological
force that can solve complex problems and shape and improve our day-to-day lives.
At the same time, the technology is highly controversial, with privacy, accuracy and its ethical use raising key concerns. Is facial recognition as inaccurate and intrusive as the media would have us believe?
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According to the British Security Industry Authority (BSIA) there is 1 CCTV camera for every 14 people in the UK. London has the second largest CCTV network (second only to Beijing) in the world and each camera has the capacity to record and store 25 pictures every second. In contrast, facial recognition only compares a single picture against a database or watchlist of pre-validated individuals.
The facial recognition system will only send an alert to the CCTV operator if a subject of interest is positively identified from the watch list. The operator can then make the final confirmation of recognition.
This can also be used to review post-event footage from one or more cameras against pre-populated watchlists. This provides a semi-automated tool for security staff to identity persons of interest in a more focused, positive and less time-consuming manner.
Over the years police super-recognisers have been successful in identifying wanted persons. Facial recognition can retrieve data in seconds so can assist them by eradicating the need to review hours of pre-recorded footage, enabling them to make speedier identifications.
If we approach this technology as a way of integrating with personnel, the technology becomes an enabler of more informed human decisions, adds another layer of authentication and retains a healthy balance between machines and people.
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