AmplitudeArrow: On-the-Go AR Menu Selection Using Consecutive Simple Head Gestures and Amplitude Visualization

Yang Tian*, Youpeng Zhang, Yukang Yan, Shengdong Zhao*, Xiaojuan Ma, Yuanchun Shi

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Heads-up computing aims to provide synergistic digital assistance that minimally interferes with users' on-the-go daily activities. Currently, the input modalities of heads-up computing are mainly voice and finger gestures. In this work, we propose and evaluate the AmplitudeArrow (AA) technique designed for on-the-go AR menu selection to demonstrate that consecutive simple head gestures can also be an effective input modality for heads-up computing. Specifically, AA arranges menu icons into one/two row(s). To select a target icon, the user first makes their head yaw to pre-select the target icon or the column containing it and then makes their head pitch to make the arrow in the target icon expand until the arrow covers the target icon completely, i.e., the pitch amplitude surpasses the selection confirmation threshold. User studies indicated that AA demonstrated robust resistance to walking-caused head perturbation and external factors such as other people/obstacles, delivering high accuracy (error rate < 5%) and fast speed (< 1.5s per selection) when there were no more than six icon columns (twelve icons) distributed horizontally and evenly in a menu area with a horizontal visual angle of 43°. © 1995-2012 IEEE.
Original languageEnglish
Pages (from-to)6870-6883
Number of pages14
JournalIEEE Transactions on Visualization and Computer Graphics
Volume31
Issue number10
Online published20 Jan 2025
DOIs
Publication statusPublished - Oct 2025

Research Keywords

  • Amplitude visualization
  • augmented reality
  • consecutive simple head gestures
  • heads-up computing
  • on-the-go menu selection

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