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Tangible UI by object and material classification with radar

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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.identifier252305883
dc.identifier6ade5f6f-ea1b-4568-b12b-7911d7afedfe
dc.identifier85040186652
dc.identifier000440716400014
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.otherORCID: /0000-0002-5274-6889/work/41757149
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.format.extent15650304
dc.language.isoeng
dc.publisherACM
dc.relation.ispartofSA '17 SIGGRAPH Asia 2017 Emerging Technologiesen
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.contributor.institutionUniversity of St Andrews. School of Computer Scienceen
dc.identifier.doihttps://doi.org/10.1145/3132818.3132824


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