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Camera-Based Selection with Cardboard Head-Mounted Displays

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HCI International 2020 – Late Breaking Papers: Virtual and Augmented Reality (HCII 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12428))

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Abstract

We present two experiments comparing selection techniques for low-cost mobile VR devices, such as Google Cardboard. Our objective was to assess the feasibility of computer vision tracking on mobile devices as an alternative to common head-ray selection methods. In the first experiment, we compared three selection techniques: air touch, head ray, and finger ray. Overall, hand-based selection (air touch) performed much worse than ray-based selection. In the second experiment, we compared different combinations of selection techniques and selection indication methods. The built-in Cardboard button worked well with the head ray technique. Using a hand gesture (air tap) with ray-based techniques resulted in slower selection times, but comparable accuracy. Our results suggest that camera-based mobile tracking is best used with ray-based techniques, but selection indication mechanisms remain problematic.

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Notes

  1. 1.

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Author information

Authors and Affiliations

  1. School of Computer Science, Carleton University, Ottawa, ON, Canada

    Siqi Luo

  2. School of Information Technology, Carleton University, Ottawa, ON, Canada

    Robert J. Teather

  3. School of Journalism and Communication, Carleton University, Ottawa, ON, Canada

    Victoria McArthur

Authors
  1. Siqi Luo
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  2. Robert J. Teather
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  3. Victoria McArthur
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Corresponding author

Correspondence to Robert J. Teather .

Editor information

Editors and Affiliations

  1. University of Crete and Foundation for Research and Technology – Hellas (FORTH), Heraklion, Crete, Greece

    Constantine Stephanidis

  2. U.S. Army Research Laboratory, Aberdeen Proving Ground, MD, USA

    Jessie Y. C. Chen

  3. U.S. Army Combat Capabilities Development Command Soldier Center, Orlando, FL, USA

    Gino Fragomeni

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Luo, S., Teather, R.J., McArthur, V. (2020). Camera-Based Selection with Cardboard Head-Mounted Displays. In: Stephanidis, C., Chen, J.Y.C., Fragomeni, G. (eds) HCI International 2020 – Late Breaking Papers: Virtual and Augmented Reality. HCII 2020. Lecture Notes in Computer Science(), vol 12428. Springer, Cham. https://doi.org/10.1007/978-3-030-59990-4_29

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  • DOI: https://doi.org/10.1007/978-3-030-59990-4_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-59989-8

  • Online ISBN: 978-3-030-59990-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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