- Security TWENTY
- Women in Security
Digital Barriers plc reports that it will be making its live facial recognition software available free to national and local authorities and agencies in the UK involved in the search for missing young people. The company’s new automatic facial recognition system, SmartVis Face, has been built around machine learning, originally with the purpose of tracking criminals and terror suspects against watch lists of thousands of people.
SmartVis Face is described by the makers as a non-conformant technology that works on standard cameras and hardware, including smartphones. In use to match faces against lists of missing young people at public spaces such as railway and bus stations, it could trigger alerts which inform relevant agencies when vulnerable young people are seen passing through. The technology will also be provided for use on smartphones that can check vulnerable young people against lists of those reported as missing.
Digital Barriers’ CEO, Zak Doffman said: “SmartVis facial recognition has been designed to significantly enhance the technology in use by law enforcement and security agencies in the fight against terrorism and serious crime. This same technology can also be used to combat the growing problem of missing and vulnerable young people passing through our towns and cities. Now we are making SmartVis facial recognition software freely available to UK agencies and authorities focusing on finding missing young people. If the agency or authority provides access to suitable cameras and PCs, we’ll do the rest. We will also make smartphone licenses freely available. At the same time we will engage with the suppliers of cameras and processing hardware to seek to engage them in this donation. Launching widespread facial recognition to help search for vulnerable missing young people is clearly an exceptional benefit of this new technology and we want to ensure that it’s widely available.”
The SmartVis Face is for use via standard smartphones, body worn cameras and CCTV cameras.