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    This study introduces a novel augmented reality (AR) object placement pipeline. Our system significantly speeds up task completion while maintaining accuracy, enhancing user experience in AR applications.

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    Area of Science:

    • Computer Science
    • Human-Computer Interaction
    • Virtual Reality

    Background:

    • Augmented Reality (AR) object placement is vital for immersive experiences.
    • A gap exists in combining user input with automated placement, considering spatial relationships.
    • Efficient object placement systems are needed for advanced AR applications.

    Purpose of the Study:

    • To present a novel object placement pipeline for AR applications.
    • To balance automated placement with user-directed control.
    • To improve efficiency and user experience in AR object placement.

    Main Methods:

    • Developed a pipeline using entity recognition, object detection, depth estimation, and spawn area allocation.
    • Evaluated the pipeline against manual placement with 50 participants.
    • Collected data through user experience questionnaires, task performance analysis, and interviews.

    Main Results:

    • The proposed pipeline significantly reduced task completion time compared to manual placement.
    • Accuracy of the automated placement was comparable to manual placement.
    • High user satisfaction was reported, with UEQ-S and TENS scores indicating positive user experience.

    Conclusions:

    • The novel AR object placement pipeline enhances task efficiency and user satisfaction.
    • Automated systems can effectively augment user-directed placement in AR.
    • This research contributes to optimizing object placement strategies in AR development.