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Direct vs. Score-based Selection: Understanding the Heisenberg Effect in Target Acquisition Across Input Modalities

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    Bare-hand virtual reality (VR) input is more prone to the Heisenberg Effect, where confirming a selection disturbs the target. A new weighted VOTE technique improves selection accuracy by considering interaction history.

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    Area of Science:

    • Human-Computer Interaction
    • Virtual Reality
    • Usability Studies

    Background:

    • Target selection is crucial in virtual reality (VR).
    • The Heisenberg Effect, where selection confirmation disturbs the target, is a known issue, primarily studied with controllers.
    • Its impact on bare-hand input and mitigation strategies are less understood.

    Purpose of the Study:

    • To investigate the Heisenberg Effect in VR using both controller and bare-hand input.
    • To compare direct and score-based selection mechanisms under the Heisenberg Effect.
    • To introduce and evaluate a novel technique, weighted VOTE, for mitigating the Heisenberg Effect.

    Main Methods:

    • A within-subject study comparing controller and hand input modalities.
    • Evaluation of direct and score-based selection mechanisms.
    • Development and temporal analysis of a history-based intention accuracy model (weighted VOTE).

    Main Results:

    • Bare-hand input is more susceptible to the Heisenberg Effect than controller input.
    • Direct selection is sensitive to target width, while score-based selection is sensitive to target density.
    • The proposed weighted VOTE method demonstrated improved selection accuracy over baseline techniques.

    Conclusions:

    • The Heisenberg Effect significantly impacts bare-hand VR interactions.
    • Input modality and selection mechanism influence susceptibility to the Heisenberg Effect.
    • Weighted VOTE offers a promising approach for adaptive target selection in VR, enhancing accuracy by accounting for interaction history.