Abstract
In this paper, we propose a novel technology called "CheekInput" with a head-mounted display (HMD) that senses touch gestures by detecting skin deformation. We attached multiple photo-reflective sensors onto the bottom front frame of the HMD. Since these sensors measure the distance between the frame and cheeks, our system is able to detect the deformation of a cheek when the skin surface is touched by fingers. Our system uses a Support Vector Machine to determine the gestures: pushing face up and down, left and right. We combined these 4 directional gestures for each cheek to extend 16 possible gestures. To evaluate the accuracy of the gesture detection, we conducted a user study. The results revealed that CheekInput achieved 80.45 % recognition accuracy when gestures were made by touching both cheeks with both hands, and 74.58 % when by touching both cheeks with one hand.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - VRST 2017 |
| Subtitle of host publication | 23rd ACM Conference on Virtual Reality Software and Technology |
| Publisher | Association for Computing Machinery |
| Volume | Part F131944 |
| ISBN (Electronic) | 9781450355483 |
| DOIs | |
| Publication status | Published - 2017 Nov 8 |
| Event | 23rd ACM Conference on Virtual Reality Software and Technology, VRST 2017 - Gothenburg, Sweden Duration: 2017 Nov 8 → 2017 Nov 10 |
Other
| Other | 23rd ACM Conference on Virtual Reality Software and Technology, VRST 2017 |
|---|---|
| Country | Sweden |
| City | Gothenburg |
| Period | 17/11/8 → 17/11/10 |
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Keywords
- OST-HMD
- Photo-reflective sensor
- Skin interface
ASJC Scopus subject areas
- Software
Cite this
CheekInput : Turning your cheek into an input surface by embedded optical sensors on a head-mounted display. / Yamashita, Koki; Kikuchi, Takashi; Masai, Katsutoshi; Sugimoto, Maki; Thomas, Bruce H.; Sugiura, Yuta.
Proceedings - VRST 2017: 23rd ACM Conference on Virtual Reality Software and Technology. Vol. Part F131944 Association for Computing Machinery, 2017. a19.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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TY - GEN
T1 - CheekInput
T2 - Turning your cheek into an input surface by embedded optical sensors on a head-mounted display
AU - Yamashita, Koki
AU - Kikuchi, Takashi
AU - Masai, Katsutoshi
AU - Sugimoto, Maki
AU - Thomas, Bruce H.
AU - Sugiura, Yuta
PY - 2017/11/8
Y1 - 2017/11/8
N2 - In this paper, we propose a novel technology called "CheekInput" with a head-mounted display (HMD) that senses touch gestures by detecting skin deformation. We attached multiple photo-reflective sensors onto the bottom front frame of the HMD. Since these sensors measure the distance between the frame and cheeks, our system is able to detect the deformation of a cheek when the skin surface is touched by fingers. Our system uses a Support Vector Machine to determine the gestures: pushing face up and down, left and right. We combined these 4 directional gestures for each cheek to extend 16 possible gestures. To evaluate the accuracy of the gesture detection, we conducted a user study. The results revealed that CheekInput achieved 80.45 % recognition accuracy when gestures were made by touching both cheeks with both hands, and 74.58 % when by touching both cheeks with one hand.
AB - In this paper, we propose a novel technology called "CheekInput" with a head-mounted display (HMD) that senses touch gestures by detecting skin deformation. We attached multiple photo-reflective sensors onto the bottom front frame of the HMD. Since these sensors measure the distance between the frame and cheeks, our system is able to detect the deformation of a cheek when the skin surface is touched by fingers. Our system uses a Support Vector Machine to determine the gestures: pushing face up and down, left and right. We combined these 4 directional gestures for each cheek to extend 16 possible gestures. To evaluate the accuracy of the gesture detection, we conducted a user study. The results revealed that CheekInput achieved 80.45 % recognition accuracy when gestures were made by touching both cheeks with both hands, and 74.58 % when by touching both cheeks with one hand.
KW - OST-HMD
KW - Photo-reflective sensor
KW - Skin interface
UR - http://www.scopus.com/inward/record.url?scp=85038595581&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85038595581&partnerID=8YFLogxK
U2 - 10.1145/3139131.3139146
DO - 10.1145/3139131.3139146
M3 - Conference contribution
AN - SCOPUS:85038595581
VL - Part F131944
BT - Proceedings - VRST 2017
PB - Association for Computing Machinery
ER -