Pinpointing: Precise Head- and Eye-Based Target Selection for Augmented Reality

Mikko Kytö, Barrett Ens, Thammathip Piumsomboon, Gun Lee, Mark Billinghurst

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

91 Citations (Scopus)

Abstract

Head and eye movement can be leveraged to improve the user’s interaction repertoire for wearable displays. Head movements are deliberate and accurate, and provide the current state-of-the-art pointing technique. Eye gaze can potentially be faster and more ergonomic, but suffers from low accuracy due to calibration errors and drift of wearable eye-tracking sensors. This work investigates precise, multimodal selection techniques using head motion and eye gaze. A comparison of speed and pointing accuracy reveals the relative merits of each method, including the achievable target size for robust selection. We demonstrate and discuss example applications for augmented reality, including compact menus with deep structure, and a proof-of-concept method for on-line correction of calibration drift.
Original languageEnglish
Title of host publicationProceedings of the 2018 CHI Conference on Human Factors in Computing Systems
PublisherACM
Pages1-14
Number of pages14
ISBN (Electronic)978-1-4503-5620-6
DOIs
Publication statusPublished - 15 Apr 2018
MoE publication typeA4 Article in a conference publication
EventACM SIGCHI Annual Conference on Human Factors in Computing Systems - Palais des Congrès de Montréal, Montreal, Canada
Duration: 21 Apr 201826 Apr 2018
Conference number: 36
https://chi2018.acm.org/
https://chi2018.acm.org

Conference

ConferenceACM SIGCHI Annual Conference on Human Factors in Computing Systems
Abbreviated titleCHI
CountryCanada
CityMontreal
Period21/04/201826/04/2018
Internet address

Keywords

  • Augmented reality
  • eye-tracking
  • head-mounted display
  • head-tracking
  • target selection
  • Gaze interaction

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