Hierarchical Radiosity with Multiresolution Meshes

Andrew J. Willmott


Thesis Committee:

Paul Heckbert, Chair
David O'Hallaron
Steven Seitz
François Sillion

(c) 2000 by Andrew Willmott


The hierarchical radiosity algorithm solves for the global transfer of diffuse illumination in a scene. While its potential algorithmic complexity is superior to both previous radiosity methods and distributed ray tracing, for scenes containing detailed polygonal models, or highly tessellated curved surfaces, its time performance and memory consumption are less than ideal. 
        My thesis is that by using hierarchies similar to those of multiresolution models, the performance of the hierarchical radiosity algorithm can be made sub-linear in the number of input polygons, and thus make radiosity on scenes containing detailed models tractable. The underlying goal of my thesis work has been to make high-speed radiosity solutions possible with such scenes. 
        To achieve this goal, a new face clustering technique for automatically partitioning polygonal models has been developed. The face clusters produced group adjacent triangles with similar normal vectors. They are used during radiosity solution to represent the light reflected by a complex object at multiple levels of detail. Also, the radiosity method is reformulated in terms of vector irradiance. Together, face clustering and the vector formulation of radiosity permit large savings. Excessively fine levels of detail are not accessed by the algorithm during the bulk of the solution phase, greatly reducing its memory requirements relative to previous methods. Consequently, the costliest steps in the simulation can be made sub-linear in scene complexity.
        I have developed a radiosity system incorporating these ideas, and shown that its performance is far superior to existing hierarchical radiosity algorithms, in the domain of scenes containing complex models. 

Online Version

The online version is available as the original postscript, and two PDF files. The smaller PDF file was produced by using the default Adobe Distiller settings. The larger file was produced by forcing Distiller to use lossless compression (zip) for all images. If you have the bandwidth, the larger file is recommended, as many images in the smaller PDF contain objectionable JPEG artifacts.

Individual Chapters

The following files are in PDF format, with lossless compression only.
Chapter 1 Introduction
Chapter 2 Previous Work on the Radiosity Problem
Chapter 3 Face Cluster Radiosity
Chapter 4 Analysis
Chapter 5 Improving the Face Cluster Construction Algorithm
Chapter 6 Implementation Details
Chapter 7 Results
Chapter 8 Conclusions


Defense Slides

Slides from my oral presentation.

Source Code

The source code that implements the methods described in the dissertation is being released at http://www.cs.cmu.edu/~ajw/thesis-code/.