Computer Science Department
School of Computer Science, Carnegie Mellon University
Hierarchical Radiosity with Multiresolution Meshes
Andrew J. Willmott
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.