[Conference][Main]

Big Data Level of Detail

Chair: Jules Bloomenthal

 Fast Polygonal Simplification with Vertex-Cluster Trees

A new data structure and algorithm for fast computation of static levels of detail, using vertex clustering and allowing adaptive simplification based on various geometric and topological criteria.

Joshua D. Mittleman
Jai Menon
IBM TJ Watson Research Center
{mittle, menon}@watson.ibm.com

 Model Simplification Using Directional Clustering

Enhancement of model simplification with a non-topographic metric and a directional clustering algorithm that uses both geometry compression and real-time, animation-dependent calculation.

Dana Marshall
A.T. Campbell, III
Donald S. Fussell
University of Texas at Austin
dane@cs.utexas.edu

 A Wavelet-Based Multiresolution Polyhedral Object Representation

Wavelet compression of a volumetric representation of polyhedral surfaces, which are represented by the zero set of a distance function.

Mike Chow
Marek Teichmann
Massachusetts Institute of Technology
{mchow,marekt}@graphics.lcs.mit.edu
http://graphics.lcs.mit.edu/~mchow

 Intelligent Transmission of 3D Polygonal Models 

A framework offering improved Level of Detail handling in VRML. Models are decomposed into fragments, which are transmitted and rendered as required to meet user-specified resolution requirements.

Peter J.C. Brown
University of Cambridge
Peter.Brown@cl.cam.ac.uk
http://www.cl.cam.ac.uk/users/pjcb2/