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    This study introduces a novel visual marker embedding method for accurate 3D projection surface pose estimation. The technique ensures markers are visible to cameras but imperceptible to humans, enabling precise image mapping.

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    Area of Science:

    • Computer Vision
    • 3D Printing
    • Robotics

    Background:

    • Accurate projection mapping onto 3D surfaces is challenging.
    • Existing methods struggle with non-planar surfaces and marker visibility.
    • Need for robust pose estimation in augmented reality and 3D display applications.

    Purpose of the Study:

    • To develop a visual marker embedding method for accurate pose estimation of 3D projection surfaces.
    • To ensure markers are detectable by infrared cameras yet imperceptible to human observers.
    • To optimize marker placement for robust stereo camera-based pose estimation.

    Main Methods:

    • Automatic embedding of visual markers on 3D printed surfaces with mechanical accuracy.
    • Designing markers for infrared camera detection on non-planar surfaces.
    • Utilizing a genetic algorithm for optimal marker placement.
    • Implementing a radiometric compensation technique to diminish marker appearance.

    Main Results:

    • Successful and accurate pose estimation of projection objects.
    • Markers were diminished to an imperceptible level for human observers.
    • Demonstrated effectiveness across various surface shapes and target textures.
    • Limitations include single-object handling and non-interactive frame rates.

    Conclusions:

    • The proposed visual marker embedding method enables accurate pose estimation for 3D projection surfaces.
    • The technique balances marker detectability with human imperceptibility.
    • Further research is needed to address multi-object handling and achieve interactive frame rates.