Show simple item record

dc.rights.licenseRestricted to current Rensselaer faculty, staff and students in accordance with the Rensselaer Standard license. Access inquiries may be directed to the Rensselaer Libraries.
dc.contributorStewart, Charles V.
dc.contributorPatterson, Stacy
dc.contributor.advisorCutler, Barbara M.
dc.contributor.authorMackenzie, Kevin
dc.date.accessioned2022-09-14T19:24:16Z
dc.date.available2022-09-14T19:24:16Z
dc.date.issued2021-08
dc.identifier.urihttps://hdl.handle.net/20.500.13015/6084
dc.descriptionAugust 2021
dc.descriptionSchool of Science
dc.description.abstractSnow 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.
dc.languageENG
dc.language.isoen_US
dc.publisherRensselaer Polytechnic Institute, Troy, NY
dc.relation.ispartofRensselaer Theses and Dissertations Online Collection
dc.subjectComputer science
dc.titleRendering snow : a light transport model for compressed anisotropic granular media
dc.typeElectronic thesis
dc.typeThesis
dc.date.updated2022-09-14T19:24:18Z
dc.rights.holderThis electronic version is a licensed copy owned by Rensselaer Polytechnic Institute (RPI), Troy, NY. Copyright of original work retained by author.
dc.description.degreeMS
dc.relation.departmentDept. of Computer Science


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record