Tangible UI by Object and Material Classification with Radar

被引：3
|
作者：
Yeo, Hui-Shyong [1 ]
Ens, Barrett [2 ]
Quigley, Aaron [1 ]
机构：
[1] Univ St Andrews, St Andrews, Fife, Scotland
[2] Univ South Australia, Adelaide, SA, Australia
来源：
SA'17: SIGGRAPH ASIA 2017 EMERGING TECHNOLOGIES | 2017年
关键词：
Radar sensing; tangible interaction; object recognition;
D O I：
10.1145/3132818.3132824
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Radar 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 UIs. 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.
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页数：2
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