Herta, has launched a new version of its facial recognition algorithms that can correctly identify people 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 (COVID19), 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 important to remember that the most differential part of the human face is in the eye area.
The launch of this software is key for the identification in automatic passenger control systems with documentation, 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 used massively in environments such as transportation, health, government, events, sports stadiums or in the gaming sector.
Herta specialises in the analysis of crowded environments, which allows to detect and identify multiple subjects at the same time through IP cameras. The company’s software is designed to be fully scalable and compatible with any IP camera, becoming an easy-to-use and accessible tool for any business organisation
