<?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="2026-06-03T15:52:43Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/B22B64ED-68AF-4357-9449-603E8D5D3D58" ns1:id="B22B64ED-68AF-4357-9449-603E8D5D3D58"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/8F4FBECB-834E-4ECB-94C5-7BD2A5497516" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/ACD7ABC9-48B0-4C5A-A2CB-AB4DC8B890AC" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/ACD7ABC9-48B0-4C5A-A2CB-AB4DC8B890AC" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/2D96324B-B991-4BBC-80CB-D97D9D41DE49" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2019-05-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/26400100-BC2F-416A-9F53-18BE8C3BCD57" ns1:rel="FUND" ns1:start="2018-03-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">133449</ns2:identifier></ns2:identifiers><ns2:title>Video action recognition in the urban environment, powered by AI and computer vision analytics</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>&amp;quot;New advances in computer vision are offering opportunities for disruptive innovation, which could have widespread benefits across multiple use cases.

The 12 month project is a partnership between Cortexica Vision Systems Ltd (artificial intelligence and computer vision experts) and Hammerson plc (owner, manager and developer of shopping centres). Cortexica have already built state of the art single image visual recognition solutions for the retail industry. This new research moves into live analysis of video.

This grant application is to develop an automated action recognition system, which uses CCTV to automatically identify &amp;quot;&amp;quot;actions&amp;quot;&amp;quot; e.g. recognising a bag/object which has been left; or identify people who slip or fall. Adopting such technology in a proactive urban safety environment, without using biometric data, could create a novel citizen-centred approach to public health and safety.&amp;quot;</ns2:abstractText></ns2:project>