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dc.contributor.authorYeo, Hui Shyong
dc.contributor.authorEns, Barrett
dc.contributor.authorQuigley, Aaron John
dc.date.accessioned2018-03-16T16:30:06Z
dc.date.available2018-03-16T16:30:06Z
dc.date.issued2017-11-27
dc.identifier.citationYeo , H S , Ens , B & Quigley , A J 2017 , Tangible UI by object and material classification with radar . in SA '17 SIGGRAPH Asia 2017 Emerging Technologies . , 14 , ACM , New York , 10th ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia , Bangkok , Thailand , 27/11/17 . https://doi.org/10.1145/3132818.3132824en
dc.identifier.citationconferenceen
dc.identifier.isbn9781450354042
dc.identifier.otherPURE: 252305883
dc.identifier.otherPURE UUID: 6ade5f6f-ea1b-4568-b12b-7911d7afedfe
dc.identifier.otherScopus: 85040186652
dc.identifier.otherORCID: /0000-0002-5274-6889/work/41757149
dc.identifier.otherWOS: 000440716400014
dc.identifier.urihttps://hdl.handle.net/10023/12965
dc.description.abstractRadar signals penetrate, scatter, absorb and reflect energy into proximate objects and ground penetrating and aerial radar systems are well established. We describe a highly accurate system based on a combination of a monostatic radar (Google Soli), supervised machine learning to support object and material classification based Uls. Based on RadarCat techniques, we explore the development of tangible user interfaces without modification of the objects or complex infrastructures. This affords new forms of interaction with digital devices, proximate objects and micro-gestures.
dc.format.extent2
dc.language.isoeng
dc.publisherACM
dc.relation.ispartofSA '17 SIGGRAPH Asia 2017 Emerging Technologiesen
dc.rights© 2017, the Owner(s) / the Author(s). This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1145/3132818.3132824en
dc.subjectRadar sensingen
dc.subjectTangible interactionen
dc.subjectObject recognitionen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectT Technologyen
dc.subjectNSen
dc.subject.lccQA75en
dc.subject.lccTen
dc.titleTangible UI by object and material classification with radaren
dc.typeConference itemen
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews. School of Computer Scienceen
dc.identifier.doihttps://doi.org/10.1145/3132818.3132824


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