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    This study introduces a new method for synthesizing realistic clouds in sky models. The data-driven approach uses artist-controlled cloud positions to generate novel cloudscapes for virtual environments.

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    Area of Science:

    • Computer graphics
    • Image synthesis
    • Computational imaging

    Background:

    • Existing sky appearance models accurately represent clear skies but lack cloud representation.
    • Clouds are crucial for realistic sky rendering in applications like image editing and virtual environments.
    • Rendering clouds into existing models is challenging due to complex light transport and representation difficulties.

    Purpose of the Study:

    • To develop a novel method for synthesizing plausible cloud appearance in sky models.
    • To enable artist control over cloud placement and density for customized cloudscapes.
    • To integrate synthesized clouds with clear-sky models for realistic lighting in virtual environments.

    Main Methods:

    • A data-driven approach using a captured dataset of high dynamic range (HDR) cloudy sky imagery.
    • Combining cloudy sky data with existing clear-sky models.
    • Developing a learned representation for synthesizing cloud appearance from coarse position data.

    Main Results:

    • Successful synthesis of plausible cloud appearance from artist-controlled representations.
    • Integration of synthesized clouds with clear-sky models for realistic lighting.
    • Rapid generation of novel and controllable cloudscapes.

    Conclusions:

    • The proposed data-driven method offers an effective alternative to rendering clouds for sky models.
    • Artist-controllable cloud synthesis facilitates the creation of diverse and realistic cloudscapes.
    • This technique enhances the realism of virtual environments by accurately representing sky conditions.