Scalable Methods for Processing Massive Geometric Meshes

86 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2005.Polygonal meshes are easily the most common surface representation currently employed in computer graphics, finding application in fields as diverse as the visual arts and scientific computation. Technological advances in the areas of three-dimensional scanning, digital storage, and computer processing speeds have enabled the acquisition of geometric meshes of unprecedented size and detail. Too large to fit in-core on most computing systems, these meshes have sizes that exceed the address space of many conventional operating systems. Efficient processing of these meshes requires fundamentally new algorithms, designed specifically for scalability. This dissertation describes novel algorithms for adaptive simplification and smoothing of massive meshes. It also proposes a new multiresolution representation for massive meshes that enables operations such as view-dependent rendering and collision detection.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD