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    Rendering snow : a light transport model for compressed anisotropic granular media

    Author
    Mackenzie, Kevin
    View/Open
    Mackenzie_rpi_0185N_11894.pdf (38.29Mb)
    Other Contributors
    Cutler, Barbara M.; Stewart, Charles V.; Patterson, Stacy;
    Date Issued
    2021-08
    Subject
    Computer science
    Degree
    MS;
    Terms of Use
    This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute (RPI), Troy, NY. Copyright of original work retained by author.;
    Metadata
    Show full item record
    URI
    https://hdl.handle.net/20.500.13015/6084
    Abstract
    Snow is a complex material that can take on many different visual properties based on the structure and shape of the individual ice grains that compose it. Individual ice grains dictate the surface texture and the transport of light through the medium as an aggregate, but simulating at this detail is computationally expensive. Existing methods for rendering granular media address this cost by approximating light transport through randomly oriented grains and only use specific individual grains to resolve surface-level details. However, they assume that grains are approximated well as a packing of non-overlapping bounding spheres, which is not always the case for snow (i.e. the classic snowflake shape). I present a light transport model that relaxes the non-overlapping requirement and enables compressed packings for highly non-spherical, anisotropic, grain shapes. It can produce snow objects that are progressively denser in appearance, both in surface detail and light transport, from sparse packings to highly compressed packings across several grain types. This model and the geometric basis I establish for compressed packings is also promising for extending the state-of-the-art granular media framework to support compressed packings of anisotropic grains.;
    Description
    August 2021; School of Science
    Department
    Dept. of Computer Science;
    Publisher
    Rensselaer Polytechnic Institute, Troy, NY
    Relationships
    Rensselaer Theses and Dissertations Online Collection;
    Access
    Restricted to current Rensselaer faculty, staff and students in accordance with the Rensselaer Standard license. Access inquiries may be directed to the Rensselaer Libraries.;
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    • RPI Theses Online (Complete)

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