We present an algorithm for interactively extracting and rendering isosurfaces of large volume datasets in a view-dependent fashion. A recursive tetrahedral mesh refinement scheme, based on longest edge bisection, is used to hierarchically decompose the data into a multiresolution structure. This data structure allows fast extraction of arbitrary isosurfaces to within user specified view-dependent error bounds. A data layout scheme based on hierarchical space filling curves provides access to the data in a cache coherent manner that follows the data access pattern indicated by the mesh refinement.
We present a new approach for reconstructing a smooth surface from a set of scattered points in three-dimensional (3D) space. Our algorithm first decomposes a given point set into a quadtree-like data structure known as a strip tree. The strip tree is used to fit a set of least squares quadratic surfaces to the data points. These quadratic surfaces are then degree-elevated to bi-cubic surfaces and blended together to form a set of B-spline surfaces that approximates the given point set.
We present an algorithm for adaptively extracting and rendering isosurfaces from compressed time-varying volume data sets. Tetrahedral meshes defined by longest edge bisection are used to create a multiresolution representation of the volume in the spatial domain that is adapted over time to approximate the time-varying volume. The reextraction of the isosurface at each time step is accelerated with the vertex programming capabilities of modern graphics hardware. A data layout scheme which follows the access pattern indicated by mesh refinement is used to access the volume in a spatially and temporally coherent manner. This data layout scheme allows our algorithm to be used for out-of-core visualization.
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