Broad Area Colloquium For AI-Geometry-Graphics-Robotics-Vision
(CS 528)

Geometry Images: Sampling Surfaces on Regular Grids

Hugues Hoppe
Microsoft Research
Monday, May 24, 2004, 4:15PM
TCSeq 200


Surfaces in graphics are commonly represented using irregular meshes, since these approximate many shapes using fewer vertices. However, their flexible connectivity comes at a price: most mesh operations require random memory accesses through vertex indices and texture coordinates; filter kernels must handle arbitrary neighborhoods; and, techniques like morphing, level-of-detail control, and compression are complicated.

In contrast, media like audio and images are represented using regular samplings - 1D and 2D grids. Such grids allow efficient traversal, random access, convolution, composition, down-sampling, compression, and synthesis. Many surface signals have now migrated into texture images. As the cost of 3D transformations becomes negligible, one should re-evaluate whether geometry itself would not be better represented using ordinary grids.

This talk will present several recent projects related to geometry images. These are constructed by parametrizing the surface over a planar domain, and resampling the surface geometry on a regular domain grid. One exciting application area is to then exploit the highly parallel GPU rasterizer to directly process geometry.

About the Speaker

Hugues Hoppe is a senior researcher in the Computer Graphics Group at Microsoft Research. His primary interests lie in the acquisition, representation, and rendering of geometric models. For his PhD work on surface reconstruction from 3D scans, he was selected as a finalist in the 1995 Discover Awards for Technological Innovation. He subsequently developed multiresolution representations for geometry, including multiresolution analysis [Eck et al 1995] for semi-regular meshing, progressive meshes [Hoppe 1996] for irregular meshing, and geometry images [Gu et al 2002] for completely regular meshing. Recent work has focused on surface parametrization, where contributions include lapped textures, normal-shooting parametrization, geometric-stretch metrics, hierarchical solvers, signal-specialized parametrization, and spherical parametrization. His most recent interest is the regular sampling of surfaces using geometry images, anticipating the unification of vertex and image buffers. His publications include 20 papers at ACM SIGGRAPH, and he is associate editor for ACM Transactions on Graphics. He is also the 2004 winner of the the ACM SIGGRAPH Achievement Award. He received a BS summa cum laude in electrical engineering in 1989 and a PhD in computer science in 1994 from the University of Washington.


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