<?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/94F3AF73-272E-40C5-B99E-CEFE2E78A9A1" ns1:id="94F3AF73-272E-40C5-B99E-CEFE2E78A9A1"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/53641DA0-FA89-41D0-8340-3AB9F2DBBC4D" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/1280AF08-A2BF-4196-8507-957870A5DE44" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/1280AF08-A2BF-4196-8507-957870A5DE44" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2022-05-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/26C68E31-00D5-448D-813B-6E3B950CB979" ns1:rel="FUND" ns1:start="2020-12-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">107443</ns2:identifier></ns2:identifiers><ns2:title>Real-time volumetric video recording of large capture areas</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>The aim of this project is to build a system capable of recording photorealistic 3D models of fast moving content in real-time, with an initial focus on sports events. When paired with virtual reality (VR), augmented reality (AR) or mixed reality (MR) hardware, these recordings will provide viewers with immersive, hologram-style renderings of events from the comfort of their own homes. The technology (known as volumetric capture) will use multiple, non intrusive sensors positioned around an event to generate the 3D reconstruction. Although the focus of this project will be on sports, the technology will be applicable to a wide range of live events. Currently, recording volumetric video of large areas (as large as or greater than the size of a boxing ring) requires processing times which prohibit live broadcasting. To enable us to record and distribute sports events in real-time, we will develop highly optimised algorithms and data structures alongside deep learning powered systems to create volumetric video of fast moving events over large areas in real-time. Working with our partner company, we will also develop camera equipment which is portable, easy to set up, and non-intrusive so as not to restrict the view of audience members.</ns2:abstractText></ns2:project>