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Empirical Evaluation of Moving Target Selection in Virtual Reality Using Egocentric Metaphors

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Human-Computer Interaction – INTERACT 2021 (INTERACT 2021)

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Abstract

Virtual hand or pointer metaphors are among the key approaches for target selection in immersive environments. However, targeting moving objects is complicated by factors including target speed, direction, and depth, such that a basic implementation of these techniques might fail to optimize user performance. We present results of two empirical studies comparing characteristics of virtual hand and pointer metaphors for moving target acquisition. Through a first study, we examine the impact of depth on users’ performance when targets move beyond and within arms’ reach. We find that movement in depth has a great impact on both metaphors. In a follow-up study, we design a reach-bounded Go-Go (rbGo-Go) technique to address challenges of virtual hand and compare it to Ray-Casting. We find that target width and speed are significant determinants of user performance and we highlight the pros and cons for each of the techniques in the given context. Our results inform the UI design for immersive selection of moving targets.

Y. Chen—The work was done when the author was an intern at Huawei Canada.

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Acknowledgements

We would like to thank Shino Che Yan for her help in creating Figs. 2, 5, and 6, Da-Yuan Huang for valuable feedback, participants for their help in this difficult time, and reviewers for valuable suggestions. This research received ethics clearance from the Office of Research Ethics, University of Waterloo. This research was funded by a grant from Waterloo-Huawei Joint Innovation Laboratory.

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Authors and Affiliations

  1. University of Waterloo, Waterloo, ON, Canada

    Yuan Chen & Edward Lank

  2. Huawei Technologies, Markham, ON, Canada

    Yuan Chen, Junwei Sun, Qiang Xu & Wei Li

  3. University of Manitoba, Winnipeg, MB, Canada

    Pourang Irani

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  1. Yuan Chen
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  2. Junwei Sun
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  3. Qiang Xu
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  4. Edward Lank
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Correspondence to Yuan Chen .

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Editors and Affiliations

  1. Department of Electrical and Information Engineering, Polytechnic University of Bari, Bari, Italy

    Carmelo Ardito

  2. Computer Science Department, University of Bari Aldo Moro, Bari, Italy

    Rosa Lanzilotti

  3. Computer Science Department, University of Pisa, Pisa, Italy

    Alessio Malizia

  4. Department of Computer Science, University of York, York, UK

    Helen Petrie

  5. Computer Science Department, University of Bari Aldo Moro, Bari, Italy

    Antonio Piccinno

  6. Computer Science Department, University of Bari Aldo Moro, Bari, Italy

    Giuseppe Desolda

  7. Microsoft Research, Redmond, WA, USA

    Kori Inkpen

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Chen, Y., Sun, J., Xu, Q., Lank, E., Irani, P., Li, W. (2021). Empirical Evaluation of Moving Target Selection in Virtual Reality Using Egocentric Metaphors. In: Ardito, C., et al. Human-Computer Interaction – INTERACT 2021. INTERACT 2021. Lecture Notes in Computer Science(), vol 12935. Springer, Cham. https://doi.org/10.1007/978-3-030-85610-6_3

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