2026-09-21T10:00:46Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/81693 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Michael Garland Shaffer, Eric Gene 2015-09-25T20:20:02Z 2015-09-25T20:20:02Z 10000-01-01 2005 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. Made available in DSpace on 2015-09-25T20:20:02Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3199137.pdf: 3311320 bytes, checksum: 3710a42ebef2ffad3e17230f601f147c (MD5) Previous issue date: 2005 Embargo set by: Seth Robbins for item 82974 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 86 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2005. http://hdl.handle.net/2142/81693 (MiAaPQ)AAI3199137 eng Computer Science Scalable Methods for Processing Massive Geometric Meshes text Computer Science Computer Science University of Illinois at Urbana-Champaign Dissertation Ph.D.