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    This study presents an automated calibration algorithm for multi-projection mapping systems using consumer hardware. The new method reduces visual artifacts like ghosting and seams, improving user experience.

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    Area of Science:

    • Computer Vision
    • Graphics and Rendering
    • Human-Computer Interaction

    Background:

    • Dynamic multi-projection mapping systems rely heavily on accurate projector-to-tracking device calibration.
    • Poor calibration leads to user-perceptible artifacts such as ghosting and seams, degrading the visual experience.
    • Existing calibration methods often require specialized, high-cost hardware.

    Purpose of the Study:

    • To introduce a novel, fully automated calibration algorithm for multi-projection mapping.
    • To reduce visual artifacts by improving calibration accuracy.
    • To achieve this using affordable, consumer-grade hardware.

    Main Methods:

    • Repurposing a structured-light scanning setup for calibration.
    • Utilizing the generated 3D model to determine intrinsic and extrinsic parameters of the system, including tracking devices.
    • A single-pass feature matching and parameter solving approach, adapted for lower-quality sensor input.

    Main Results:

    • Successfully developed and demonstrated a fully automated calibration algorithm.
    • The algorithm effectively reduces common artifacts like ghosting and seams in multi-projection mapping.
    • The system operates effectively with consumer-grade hardware, lowering the barrier to entry.

    Conclusions:

    • The proposed automated calibration method significantly enhances the quality of dynamic multi-projection mapping systems.
    • Repurposing structured-light scanning offers an effective and economical solution for calibration.
    • This approach democratizes high-quality projection mapping by utilizing accessible hardware.