The world’s driving company in facial acknowledgment arrangements for swarmed situations, Herta, is propelling this week a modern form of its facial acknowledgment calculations that can accurately distinguish individuals who wear facial masks.
The company had been working on the issue of partial occlusions for some time and, following the worldwide outbreak of coronavirus (COVID-19), development has been accelerated to launch a version of the software that helps provide an accurate identification under these conditions.
Based on Deep Learning technology, Herta’s algorithms provide very high identification rates, especially in identity verification tasks and their reliability is very high, even when people hide a large part of their face. It is worth noting that the most differential part of the human face is in the eye region.
The launch of this software is key for automatic passenger identification systems, such as border control with the passport. This way it will not be necessary for the person to remove the mask, avoiding possible contagion or long waiting times. Its application, in general, extends to any type of access control or identity verification system.
Herta expects that the impact of this new technology in the market will be very important worldwide and that it will be massively used in environments such as transportation, health, government, events, sports stadiums or in the gaming sector.