<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-07-08T08:44:08Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/465AAD53-23B3-41C7-A581-54F8D2871BB0" ns1:id="465AAD53-23B3-41C7-A581-54F8D2871BB0"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/118E513B-060B-45B2-B65F-D92FE2ABC338" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/DF2685F5-C5B7-4883-81DE-8947FF6EC88A" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/D9C9A6E7-18BD-4B4A-BEC5-8575623C0DE4" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/DF2685F5-C5B7-4883-81DE-8947FF6EC88A" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2016-03-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/F8BEE784-4610-4F0C-88B9-A9689F4E7430" ns1:rel="FUND" ns1:start="2015-03-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">131825</ns2:identifier></ns2:identifiers><ns2:title>Project COMVIDIA: COrrelated Movement and Video ID Authentication</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Project COMVIDIA creates an innovative new identity assurance technology, capable of being used as a distinctive factor in a highly secure multi-factor authentication solution, or to offer users a simple substitute for CAPTCHA-type mechanisms, which restrict system access for human-only entry. The technology combines extreme simplicity for the user with scalable security for the service provider, enabling a wide range of applications. The project builds on insights gained by lead partner iProov in the course of innovating world-class ‘ID as a Service’ technology, and from new research and experiments in image processing using novel ‘Eulerian video’, a method of magnifying human features in order to detect characteristics of human liveness. iProov will investigate image science and other aspects of pre-industrial research, and The Media Institute (a wholly-owned entity of University College London) will collaborate on validation of the approach, providing advanced usability testing.</ns2:abstractText></ns2:project>