Evaluation of Grasp Posture Detection Method using Corneal Reflection Images through a Crowdsourced Experiment

Xiang Zhang, Kaori Ikematsu, Kunihiro Kato, Yuta Sugiura

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationISS 2022 - Companion Proceedings of the 2022 Conference on Interactive Surfaces and Spaces
EditorsCraig Anslowx, Judy Kay
PublisherAssociation for Computing Machinery, Inc
Pages9-13
Number of pages5
ISBN (Electronic)9781450393560
DOIs
Publication statusPublished - 2022 Nov 20
Event2022 ACM International Conference on Interactive Surfaces and Spaces, ISS 2022 - Wellington, New Zealand
Duration: 2022 Nov 202022 Nov 23

Publication series

NameISS 2022 - Companion Proceedings of the 2022 Conference on Interactive Surfaces and Spaces

Conference

Conference2022 ACM International Conference on Interactive Surfaces and Spaces, ISS 2022
Country/TerritoryNew Zealand
CityWellington
Period22/11/2022/11/23

Keywords

  • Corneal reflection images
  • Crowdsourced experiment.
  • Hand grip detection

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