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Crowdsourcing Design Guidance for Contextual Adaptation of Text Content in Augmented Reality

John J. Dudley,Jason T. Jacques,P. Kristensson

Published 2021 in International Conference on Human Factors in Computing Systems

ABSTRACT

Augmented Reality (AR) can deliver engaging user experiences that seamlessly meld virtual content with the physical environment. However, building such experiences is challenging due to the developer’s inability to assess how uncontrolled deployment contexts may influence the user experience. To address this issue, we demonstrate a method for rapidly conducting AR experiments and real-world data collection in the user’s own physical environment using a privacy-conscious mobile web application. The approach leverages the large number of distinct user contexts accessible through crowdsourcing to efficiently source diverse context and perceptual preference data. The insights gathered through this method complement emerging design guidance and sample-limited lab-based studies. The utility of the method is illustrated by re-examining the design challenge of adapting AR text content to the user’s environment. Finally, we demonstrate how gathered design insight can be operationalized to provide adaptive text content functionality in an AR headset.

PUBLICATION RECORD

  • Publication year

    2021

  • Venue

    International Conference on Human Factors in Computing Systems

  • Publication date

    2021-05-06

  • Fields of study

    Computer Science

  • Identifiers
    DOI 10.1145/3411764.3445493
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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