Moving Target Selection: A Cue Integration Model

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

doi:10.1145/3173574.3173804

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 proceeding › Conference contribution › Scientific › peer-review

33 Citations (Scopus)

215 Downloads (Pure)

Abstract

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 language	English
Title of host publication	Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Place of Publication	New York, NY, USA
Publisher	ACM
ISBN (Print)	978-1-4503-5620-6
DOIs	https://doi.org/10.1145/3173574.3173804
Publication status	Published - 2018
MoE publication type	A4 Article in a conference publication
Event	ACM SIGCHI Annual Conference on Human Factors in Computing Systems - Palais des Congrès de Montréal, Montreal, Canada Duration: 21 Apr 2018 → 26 Apr 2018 Conference number: 36 https://chi2018.acm.org/ https://chi2018.acm.org

Conference

Conference	ACM SIGCHI Annual Conference on Human Factors in Computing Systems
Abbreviated title	CHI
Country/Territory	Canada
City	Montreal
Period	21/04/2018 → 26/04/2018
Internet address	https://chi2018.acm.org/ https://chi2018.acm.org

Keywords

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

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10.1145/3173574.3173804

ELEC-Lee-et-al-Moving target_CHI2018Final published version, 2.58 MB

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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.
27/03/2015 → 31/03/2020
Project: EU: ERC grants

Cite this

@inproceedings{eb728982f9bd466d8f8069c74e9cf845,

title = "Moving Target Selection: A Cue Integration Model",

abstract = "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.",

keywords = "Temporal pointing, player modeling, moving target selection, level of difficulty, game balancing, cue integration",

author = "Byungjoo Lee and Sunjun Kim and Antti Oulasvirta and Jong-In Lee and Eunji Park",

note = "| openaire: EC/H2020/637991/EU//COMPUTED; ACM SIGCHI Annual Conference on Human Factors in Computing Systems, CHI ; Conference date: 21-04-2018 Through 26-04-2018",

year = "2018",

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isbn = "978-1-4503-5620-6",

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T2 - ACM SIGCHI Annual Conference on Human Factors in Computing Systems

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AU - Kim, Sunjun

AU - Oulasvirta, Antti

AU - Lee, Jong-In

AU - Park, Eunji

N1 - Conference code: 36

PY - 2018

Y1 - 2018

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AB - 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.

KW - Temporal pointing

KW - player modeling

KW - moving target selection

KW - level of difficulty

KW - game balancing

KW - cue integration

U2 - 10.1145/3173574.3173804

DO - 10.1145/3173574.3173804

M3 - Conference contribution

SN - 978-1-4503-5620-6

BT - Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

PB - ACM

CY - New York, NY, USA

Y2 - 21 April 2018 through 26 April 2018

ER -

Moving Target Selection: A Cue Integration Model

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Conference

Keywords

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COMPUTED: Computational User Interface Design

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