TY - GEN
T1 - Evaluation of Grasp Posture Detection Method using Corneal Reflection Images through a Crowdsourced Experiment
AU - Zhang, Xiang
AU - Ikematsu, Kaori
AU - Kato, Kunihiro
AU - Sugiura, Yuta
N1 - Funding Information:
Thiswork was supported by JST PRESTOGrant Number JPMJPR2134.
Funding Information:
This work was supported by JST PRESTO Grant Number JPMJPR2134.
Publisher Copyright:
© 2022 ACM.
PY - 2022/11/20
Y1 - 2022/11/20
N2 - To achieve adaptive user interfaces (UI) for smartphones, researchers have been developing sensing methods to detect how a user is holding a smartphone. A variety of promising adaptive UIs have been demonstrated, such as those that automatically switch the displayed content and the position of interactive components in accordance with how the phone is being held. In this paper, we present a follow-up study on ReflecTouch, a state-of-The-Art grasping posture detection method proposed by Zhang et al.That uses corneal reflection images captured by the front camera of a smartphone. We extend the previous work by investigating the performance of this method towards actual use and its potential challenges through a crowdsourced experiment with a large number of participants.
AB - To achieve adaptive user interfaces (UI) for smartphones, researchers have been developing sensing methods to detect how a user is holding a smartphone. A variety of promising adaptive UIs have been demonstrated, such as those that automatically switch the displayed content and the position of interactive components in accordance with how the phone is being held. In this paper, we present a follow-up study on ReflecTouch, a state-of-The-Art grasping posture detection method proposed by Zhang et al.That uses corneal reflection images captured by the front camera of a smartphone. We extend the previous work by investigating the performance of this method towards actual use and its potential challenges through a crowdsourced experiment with a large number of participants.
KW - Corneal reflection images
KW - Crowdsourced experiment.
KW - Hand grip detection
UR - http://www.scopus.com/inward/record.url?scp=85146268360&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85146268360&partnerID=8YFLogxK
U2 - 10.1145/3532104.3571457
DO - 10.1145/3532104.3571457
M3 - Conference contribution
AN - SCOPUS:85146268360
T3 - ISS 2022 - Companion Proceedings of the 2022 Conference on Interactive Surfaces and Spaces
SP - 9
EP - 13
BT - ISS 2022 - Companion Proceedings of the 2022 Conference on Interactive Surfaces and Spaces
A2 - Anslowx, Craig
A2 - Kay, Judy
PB - Association for Computing Machinery, Inc
T2 - 2022 ACM International Conference on Interactive Surfaces and Spaces, ISS 2022
Y2 - 20 November 2022 through 23 November 2022
ER -