Tangible UI by object and material classification with radar

Hui Shyong Yeo; Barrett Ens; Aaron Quigley

doi:10.1145/3132818.3132824

Tangible UI by object and material classification with radar

Hui Shyong Yeo, Barrett Ens, Aaron Quigley

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other › peer-review

4 Citations (Scopus)

Abstract

Radar signals penetrate, scaffer, 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.

Original language	English
Title of host publication	Proceeding SA'17 - SIGGRAPH Asia 2017 Emerging Technologies
Subtitle of host publication	Bangkok, Thailand — November 27 - 30, 2017
Editors	Takuji Narumi, Borom Tunwattanapong
Place of Publication	New York NY USA
Publisher	Association for Computing Machinery (ACM)
Number of pages	2
ISBN (Electronic)	9781450354042
DOIs	https://doi.org/10.1145/3132818.3132824
Publication status	Published - 2017
Externally published	Yes
Event	ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia 2017 - Bangkok, Thailand Duration: 27 Nov 2017 → 30 Nov 2017 Conference number: 10th https://sa2017.siggraph.org/

Conference

Conference	ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia 2017
Abbreviated title	SIGGRAPH Asia 2017
Country/Territory	Thailand
City	Bangkok
Period	27/11/17 → 30/11/17
Internet address	https://sa2017.siggraph.org/

Keywords

Object recognition
Radar sensing
Tangible interaction

Access to Document

10.1145/3132818.3132824

Cite this

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title = "Tangible UI by object and material classification with radar",

abstract = "Radar signals penetrate, scaffer, 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.",

keywords = "Object recognition, Radar sensing, Tangible interaction",

author = "Yeo, {Hui Shyong} and Barrett Ens and Aaron Quigley",

year = "2017",

doi = "10.1145/3132818.3132824",

language = "English",

editor = "Narumi, {Takuji } and Tunwattanapong, {Borom }",

booktitle = "Proceeding SA'17 - SIGGRAPH Asia 2017 Emerging Technologies",

publisher = "Association for Computing Machinery (ACM)",

address = "United States of America",

note = "ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia 2017, SIGGRAPH Asia 2017 ; Conference date: 27-11-2017 Through 30-11-2017",

url = "https://sa2017.siggraph.org/",

}

Yeo, HS, Ens, B & Quigley, A 2017, Tangible UI by object and material classification with radar. in T Narumi & B Tunwattanapong (eds), Proceeding SA'17 - SIGGRAPH Asia 2017 Emerging Technologies: Bangkok, Thailand — November 27 - 30, 2017., 14, Association for Computing Machinery (ACM), New York NY USA, ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia 2017, Bangkok, Thailand, 27/11/17. https://doi.org/10.1145/3132818.3132824

Tangible UI by object and material classification with radar. / Yeo, Hui Shyong; Ens, Barrett; Quigley, Aaron.
Proceeding SA'17 - SIGGRAPH Asia 2017 Emerging Technologies: Bangkok, Thailand — November 27 - 30, 2017. ed. / Takuji Narumi; Borom Tunwattanapong. New York NY USA: Association for Computing Machinery (ACM), 2017. 14.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other › peer-review

TY - GEN

T1 - Tangible UI by object and material classification with radar

AU - Yeo, Hui Shyong

AU - Ens, Barrett

AU - Quigley, Aaron

N1 - Conference code: 10th

PY - 2017

Y1 - 2017

N2 - Radar signals penetrate, scaffer, 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.

AB - Radar signals penetrate, scaffer, 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.

KW - Object recognition

KW - Radar sensing

KW - Tangible interaction

UR - http://www.scopus.com/inward/record.url?scp=85040186652&partnerID=8YFLogxK

U2 - 10.1145/3132818.3132824

DO - 10.1145/3132818.3132824

M3 - Conference Paper

AN - SCOPUS:85040186652

BT - Proceeding SA'17 - SIGGRAPH Asia 2017 Emerging Technologies

A2 - Narumi, Takuji

A2 - Tunwattanapong, Borom

PB - Association for Computing Machinery (ACM)

CY - New York NY USA

T2 - ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia 2017

Y2 - 27 November 2017 through 30 November 2017

ER -

Tangible UI by object and material classification with radar

Abstract

Conference

Keywords

Access to Document

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Cite this