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    This study introduces a new method to create 3D cloud models from sky images, improving computer vision and imaging applications by capturing volumetric cloud properties for realistic lighting and shadows.

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    Area of Science:

    • Computer Vision
    • Computer Graphics
    • Atmospheric Optics

    Background:

    • Accurate sky illumination is vital for imaging and vision systems.
    • Existing methods for sky illumination often simplify clouds or assume distant lighting, neglecting their 3D structure.
    • Representing complex cloud illumination remains a significant challenge in computer graphics and vision.

    Purpose of the Study:

    • To develop a novel method for extracting 3D volumetric representations of clouds from single sky images.
    • To enable more realistic and accurate sky illumination for various imaging applications.
    • To overcome the limitations of existing methods that do not capture the 3D properties of clouds.

    Main Methods:

    • A single fisheye sky capture is used as input.
    • An iterative optimization process extracts 3D cloud geometry and properties.
    • The method leverages physical light scattering principles and a domain-specific light transport simulation for optimization.

    Main Results:

    • The reconstructed 3D clouds achieve high accuracy when re-rendered compared to real captures.
    • The approach enables novel applications, including rendering with captured clouds and simulating cloud shadows.
    • Improved aerial perspective and lighting accuracy are demonstrated.

    Conclusions:

    • The proposed method successfully extracts accurate 3D volumetric cloud representations from single images.
    • This technique significantly enhances the realism and applicability of sky illumination in imaging and computer graphics.
    • The extracted 3D cloud data opens new possibilities for realistic scene rendering and analysis.