Moving Target Selection: A Cue Integration Model

Byungjoo Lee, Sunjun Kim, Antti Oulasvirta, Jong-In Lee, Eunji Park

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

33 Citations (Scopus)
215 Downloads (Pure)


This paper investigates a common task requiring temporal precision: the selection of a rapidly moving target on display by invoking an input event when it is within some selection window. Previous work has explored the relationship between accuracy and precision in this task, but the role of visual cues available to users has remained unexplained. To expand modeling of timing performance to multimodal settings, common in gaming and music, our model builds on the principle of probabilistic cue integration. Maximum likelihood estimation (MLE) is used to model how different types of cues are integrated into a reliable estimate of the temporal task. The model deals with temporal structure (repetition, rhythm) and the perceivable movement of the target on display. It accurately predicts error rate in a range of realistic tasks. Applications include the optimization of difficulty in game-level design.
Original languageEnglish
Title of host publicationProceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Place of PublicationNew York, NY, USA
ISBN (Print)978-1-4503-5620-6
Publication statusPublished - 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


ConferenceACM SIGCHI Annual Conference on Human Factors in Computing Systems
Abbreviated titleCHI
Internet address


  • Temporal pointing
  • player modeling
  • moving target selection
  • level of difficulty
  • game balancing
  • cue integration


Dive into the research topics of 'Moving Target Selection: A Cue Integration Model'. Together they form a unique fingerprint.
  • COMPUTED: Computational User Interface Design

    Feit, A., Oulasvirta, A., Todi, K., Dayama, N., Koch, J., Nancel, M., Brückner, L., Liao, Y., Shiripour, M., Leiva, L., Nioche, A. & Kim, S.


    Project: EU: ERC grants

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