title: Streaming simplification of tetrahedral meshes.
abstract: Unstructured tetrahedral meshes are commonly used in scientific computing to represent scalar, vector, and tensor fields in three dimensions. Visualization of these meshes can be difficult to perform interactively due to their size and complexity. By reducing the size of the data, we can accomplish real-time visualization necessary for scientific analysis. We propose a two-step approach for streaming simplification of large tetrahedral meshes. Our algorithm arranges the data on disk in a streaming, I/O-efficient format that allows coherent access to the tetrahedral cells. A quadric-based simplification is sequentially performed on small portions of the mesh in-core. Our output is a coherent streaming mesh which facilitates future processing. Our technique is fast, produces high quality approximations, and operates out-of-core to process meshes too large for main memory.
authors.affiliation: Scientific Computing and Imaging Institute, Salt Lake City, UT 84112, USA. hvo@sci.utah.edu
authors.forename: Huy T
authors.initials: HT
authors.lastname: Vo
authors.forename: Steven P
authors.initials: SP
authors.lastname: Callahan
authors.forename: Peter
authors.initials: P
authors.lastname: Lindstrom
authors.forename: Valerio
authors.initials: V
authors.lastname: Pascucci
authors.forename: Cláudio T
authors.initials: CT
authors.lastname: Silva
mesh_terms: D000465:Algorithms; D003196:Computer Graphics; D003199:Computer Systems; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D014584:User-Computer Interface