Spain-based facial recognition company Herta has announced it is launching a new version of its facial recognition algorithm that is able to identify people wearing masks.
This comes as the world is dealing with the outbreak of COVID-19, which was recently declared a pandemic by the World Health Organization (WHO). Herta had been working on this issue before the outbreak of COVID-19, though it accelerated its development to facilitate a launch during a time when the wearing of masks is likely to increase. COVID-19 is a highly contagious viral infection, necessitating the wearing of protective masks by front-line health-care workers providing testing and treatment to the rising number of infected.
Using Deep Learning technology, Herta’s algorithms provide high identification rates, particularly with regards to identifying individuals hiding the majority of their face. The company notes that the eye region is the most important in terms of differentiating people.
Facial recognition systems are key tools in automatic passenger identification processes, and are increasingly relied upon for border control in airports across the world. Enabling these systems to work effectively without requiring people to remove a mask could potentially help with reducing the spread of a virus like COVID-19 and consequently reduce waiting times at access control points.
Health officials have also cautioned against public gatherings, as they are likely to accelerate the spread of the virus.
The majority of professional and amatuer sports leagues — including the NBA, MLB and NHL in North America, and professional soccer leagues across the globe — have suspended play or delayed the start of new seasons to prevent large public gatherings from increasing the spread of COVID-19.
It’s possible that when these leagues resume, many spectators will choose to wear masks while attending events, as caution will likely be heightened.
March 13, 2020 – by Tony Bitzionis