Understanding the uncertainty in 1D unidirectional moving target selection

Jin Huang, Xiaolong Zhang, Feng Tian, Xiangmin Fan, Shumin Zhai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In contrast to the extensive studies on static target pointing, much less formal understanding of moving target acquisition can be found in the HCI literature. We designed a set of experiments to identify regularities in 1D unidirectional moving target selection, and found a Ternary-Gaussian model to be descriptive of the endpoint distribution in such tasks. The shape of the distribution as characterized by μ and ω in the Gaussian model were primarily determined by the speed and size of the moving target. The model fits the empirical data well with 0.95 and 0.94 R2 values for μ and ω, respectively. We also demonstrated two extensions of the model, including 1) predicting error rates in moving target selection; and 2) a novel interaction technique to implicitly aid moving target selection. By applying them in a game interface design, we observed good performances in both predicting error rates (e.g., 2.7% mean absolute error) and assisting moving target selection (e.g., 33% or a greater increase in pointing accuracy).

Original languageEnglish (US)
Title of host publicationCHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems
Subtitle of host publicationEngage with CHI
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450356206, 9781450356213
DOIs
StatePublished - Apr 20 2018
Event2018 CHI Conference on Human Factors in Computing Systems, CHI 2018 - Montreal, Canada
Duration: Apr 21 2018Apr 26 2018

Publication series

NameConference on Human Factors in Computing Systems - Proceedings
Volume2018-April

Other

Other2018 CHI Conference on Human Factors in Computing Systems, CHI 2018
CountryCanada
CityMontreal
Period4/21/184/26/18

Fingerprint

Human computer interaction
Uncertainty
Experiments

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

Cite this

Huang, J., Zhang, X., Tian, F., Fan, X., & Zhai, S. (2018). Understanding the uncertainty in 1D unidirectional moving target selection. In CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems: Engage with CHI (Conference on Human Factors in Computing Systems - Proceedings; Vol. 2018-April). Association for Computing Machinery. https://doi.org/10.1145/3173574.3173811
Huang, Jin ; Zhang, Xiaolong ; Tian, Feng ; Fan, Xiangmin ; Zhai, Shumin. / Understanding the uncertainty in 1D unidirectional moving target selection. CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems: Engage with CHI. Association for Computing Machinery, 2018. (Conference on Human Factors in Computing Systems - Proceedings).
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Huang, J, Zhang, X, Tian, F, Fan, X & Zhai, S 2018, Understanding the uncertainty in 1D unidirectional moving target selection. in CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems: Engage with CHI. Conference on Human Factors in Computing Systems - Proceedings, vol. 2018-April, Association for Computing Machinery, 2018 CHI Conference on Human Factors in Computing Systems, CHI 2018, Montreal, Canada, 4/21/18. https://doi.org/10.1145/3173574.3173811

Understanding the uncertainty in 1D unidirectional moving target selection. / Huang, Jin; Zhang, Xiaolong; Tian, Feng; Fan, Xiangmin; Zhai, Shumin.

CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems: Engage with CHI. Association for Computing Machinery, 2018. (Conference on Human Factors in Computing Systems - Proceedings; Vol. 2018-April).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Huang J, Zhang X, Tian F, Fan X, Zhai S. Understanding the uncertainty in 1D unidirectional moving target selection. In CHI 2018 - Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems: Engage with CHI. Association for Computing Machinery. 2018. (Conference on Human Factors in Computing Systems - Proceedings). https://doi.org/10.1145/3173574.3173811