<?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/9AB84DF0-60F9-41F2-9DFF-637C036A246B" ns1:id="9AB84DF0-60F9-41F2-9DFF-637C036A246B"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/915193B3-BDAD-484E-80F2-6EC5AFEF08F1" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/9F2B4154-8326-41A9-8036-A954A9C7138E" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/9F2B4154-8326-41A9-8036-A954A9C7138E" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2013-11-30T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/26BC288B-BBC9-4291-8131-EA4D3440570D" ns1:rel="FUND" ns1:start="2013-07-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">131379</ns2:identifier></ns2:identifiers><ns2:title>Human-Computer Interaction through Hand Gesture Recognition</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Hand gesture recognition (HGR) is a fast emerging technology (FET) for facilitating Human-Computer Interaction (HCI). The past few years have seen attempts to exploit its potential in applications such as gaming, sign language recognition, contactless medical document browsing, assisted living and virtual fitting room. However, at the current infant stage of this FET, the common limitations of the existing hand gesture recognition techniques are 1) rigid constraints: the hand movement of a complete gesture has to be in view of the camera, 2) high ambiguity: the similarity between sub-gestures of different gestures may be so high that confusions occur frequently, 3) high computational complexity, and 4) high sensitivity to foregournd and background human interference. It is our intention in this project to study the feasibility of a new efficient hand gesture recognition technique that is able to alleviate those limitations.</ns2:abstractText></ns2:project>