research-article

Modeling the Endpoint Uncertainty in Crossing-based Moving Target Selection

Authors:

Hongan WangAuthors Info & Claims

CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Pages 1 - 12

https://doi.org/10.1145/3313831.3376336

Published: 23 April 2020 Publication History

Abstract

Modeling the endpoint uncertainty of moving target selection with crossing is essential to understand factors such as speed-accuracy trade-off and interaction efficiency in crossing-based user interfaces with dynamic contents. However, there have been few studies looking into this research topic in the HCI field. This paper presents a Quaternary-Gaussian model to quantitatively measure the endpoint uncertainty in crossing-based moving target selection. To validate this model, we conducted an experiment with discrete crossing tasks on five factors, i.e., initial distance, size, speed, orientation, and moving direction. Results showed that our model fit the data of μ and σ accurately with adjusted R2 of 0.883 and 0.920. We also demonstrated the validity of our model in predicting error rates in crossing-based moving target selection. We concluded with a set of implications for future designs.

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Cited By

Yamanaka SUsuba H(2024)0.2-mm-Step Verification of the Dual Gaussian Distribution Model with Large Sample Size for Predicting Tap Success RatesProceedings of the ACM on Human-Computer Interaction10.1145/36981538:ISS(674-693)Online publication date: 24-Oct-2024
https://dl.acm.org/doi/10.1145/3698153
Khan SDevlen CManno MHou D(2024)Mouse Dynamics Behavioral Biometrics: A SurveyACM Computing Surveys10.1145/364031156:6(1-33)Online publication date: 24-Jan-2024
https://dl.acm.org/doi/10.1145/3640311
Lee DKim SNoh JLee B(2024)User Performance in Consecutive Temporal Pointing: An Exploratory StudyProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642904(1-15)Online publication date: 11-May-2024
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Index Terms

Modeling the Endpoint Uncertainty in Crossing-based Moving Target Selection
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI theory, concepts and models

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cover image ACM Conferences

CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

April 2020

10688 pages

ISBN:9781450367080

DOI:10.1145/3313831

General Chairs:
Regina Bernhaupt
Eindhoven University of Technology, Netherlands
,
Florian 'Floyd' Mueller
Monash University, Australia
,
David Verweij
Newcastle University, UK
,
Josh Andres
RMIT, Australia
,
Program Chairs:
Joanna McGrenere
University of British Columbia, Canada
,
Andy Cockburn
University of Canterbury, New Zealand
,
Ignacio Avellino
University of Maryland Baltimore County, USA
,
Alix Goguey
Grenoble Alpes University, France
,
Pernille Bjørn
University of Copenhagen, Denmark
,
Shengdong (Shen) Zhao
National University of Singapore, Singapore
,
Briane Paul Samson
Future University Hakodate, Japan & De La Salle University, Philippines
,
Rafal Kocielnik
University of Washington, USA

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Published: 23 April 2020

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Youth Innovation Promotion Association CAS
National Key R&D Program of China
National Natural Science Foundation of China

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CHI '20: CHI Conference on Human Factors in Computing Systems

April 25 - 30, 2020

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Cited By

Yamanaka SUsuba H(2024)0.2-mm-Step Verification of the Dual Gaussian Distribution Model with Large Sample Size for Predicting Tap Success RatesProceedings of the ACM on Human-Computer Interaction10.1145/36981538:ISS(674-693)Online publication date: 24-Oct-2024
https://dl.acm.org/doi/10.1145/3698153
Khan SDevlen CManno MHou D(2024)Mouse Dynamics Behavioral Biometrics: A SurveyACM Computing Surveys10.1145/364031156:6(1-33)Online publication date: 24-Jan-2024
https://dl.acm.org/doi/10.1145/3640311
Lee DKim SNoh JLee B(2024)User Performance in Consecutive Temporal Pointing: An Exploratory StudyProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642904(1-15)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642904
Shi YYi XLiang CQin YWang YYan YCheng ZZhu PZhang SLi YLiu YWang XChen JZhou WWang YZhao DDu F(2024)HCI Research and Innovation in China: A 10-Year PerspectiveInternational Journal of Human–Computer Interaction10.1080/10447318.2024.232385840:8(1799-1831)Online publication date: 22-Mar-2024
https://doi.org/10.1080/10447318.2024.2323858
Li YLiu JHuang JZhang YPeng XBian YTian F(2024)Evaluating the effects of user motion and viewing mode on target selection in augmented realityInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2024.103327191:COnline publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1016/j.ijhcs.2024.103327
Wei YShi RYu DWang YLi YYu LLiang H(2023)Predicting Gaze-based Target Selection in Augmented Reality Headsets based on Eye and Head Endpoint DistributionsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581042(1-14)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581042
Yamanaka SUsuba H(2023)Tuning Endpoint-variability Parameters by Observed Error Rates to Obtain Better Prediction Accuracy of Pointing MissesProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580746(1-18)Online publication date: 19-Apr-2023
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Yamanaka SUsuba HTakahashi HMiyashita H(2023)Predicting Success Rates in Steering Through Linear and Circular Paths by the Servo-Gaussian ModelInternational Journal of Human–Computer Interaction10.1080/10447318.2023.221222140:16(4300-4318)Online publication date: 18-May-2023
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Usuba HYamanaka SSato JMiyashita H(2022)Predicting Touch Accuracy for Rectangular Targets by Using One-Dimensional Task ResultsProceedings of the ACM on Human-Computer Interaction10.1145/35677326:ISS(525-537)Online publication date: 14-Nov-2022
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Usuba HYamanaka SMiyashita H(2021)Modeling Movement Times and Success Rates for Acquisition of One-dimensional Targets with Uncertain Touchable SizesProceedings of the ACM on Human-Computer Interaction10.1145/34869535:ISS(1-15)Online publication date: 5-Nov-2021
https://dl.acm.org/doi/10.1145/3486953
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