Reference: SIGGRAPH 1993 Education Slide Set, by Stephen Spencer

## Slide 14 : Progressive Radiosity Variants.

Several variations on the basic progressive radiosity algorithm have been developed, in an effort to find the optimal method for producing the most pleasing results with minimum cost. Each variant calculates the form factors from a point on one surface to all other surfaces.

The "gathering" variant collects light energy from all other surfaces in the environment, attenuated by the calculated form factors, and updates the "base" surface. In this variant, as well as the "shooting" variant, the "base" surface is arbitrarily chosen.

The "shooting" variant distributes light energy from the "base" surface to all other surfaces in the environment, attenuated by the calculated form factors.

The "shooting and sorting" variant first calculates the surface with the greatest amount of unshot light energy, then uses this surface as the "base" surface in the "shooting" variant.

In addition to these, an initial "ambient" term can be approximated for the environment and adjusted at each iteration, gradually replaced by the true ambient contribution to the rendered image.

The "shooting and sorting" method is the most desirable, as it finds the surface with the greatest potential contribution to the intensity solution and updates all other surfaces in the environment with its energy.

## Slide 15 : Comparison of Progressive Variants.

This slide shows four variations on the basic progressive radiosity algorithm, each halted after one hundred iterations. The upper left image is the "gathering" variant, the upper right image the "shooting" variant, the lower left image the "shooting and sorting" variant, and the lower right image is the "shooting and sorting and ambient" progressive radiosity variant.

The "shooting" variants show their superiority over the "gathering" variant here, as more of the scene is illuminated by them earlier. The "shooting and sorting" variant's concentration on those surfaces which contribute most to the overall solution is also shown.

## Slide 16: The Two-Pass Radiosity Solution.

Several important variations on the basic diffuse radiosity solution have been developed. The first is designed to relax the restriction on the diffuse-only nature of the basic radiosity solution, by breaking the intensity solution into two steps: first, a pass with a traditional radiosity algorithm to calculate the diffuse intensity of the surfaces, followed by a pass with a ray tracing algorithm, which collects the diffuse intensity information from the surfaces and adds to it specular information. This second pass is viewpoint- dependent: specular highlights on a surface are dependent on the location of both the light and the viewer relative to the surface.

## Slide 17 : Participating Media.

Another variation on the basic diffuse radiosity solution adds the contribution of light passing through a participating medium, such as smoke, fog, or water vapor in the air.

In this algorithm, light energy is sent through a three-dimensional volume representing a participating medium, which both attenuates the light energy and, potentially, adds to the intensity solution through illumination of the participating medium.

The largest single advantage of the radiosity method for computer image generation is the highly realistic quality of the resulting images. No other method accurately calculates the diffuse interreflection of light energy in an environment. Soft shadows and color bleeding are natural by-products of this method, just as hard shadows and mirror-like reflections are natural by-products of a typical ray-tracing algorithm.

In addition to being visually pleasing, the method can be quite accurate in its treatment of energy transport between surfaces.

The viewpoint independence of the basic radiosity algorithm provides the opportunity for interactive "walkthroughs" of environments, as one intensity solution for an environment will serve as the base for any particular view of the environment.

The costs associated with the radiosity method are substantial. The "full matrix" radiosity method requires a large amount of storage and long computation times for form factor calculation and matrix solution. The "progressive" method must also calculate a large number of form factors, many more than once.

Accuracy in the resulting intensity solution requires preprocessing the environment, subdividing large surfaces into a set of smaller surfaces, and more surfaces means more storage and computation.

## Slide 19 : State Of The Art / Future Work.

More recently, several new algorithms have been developed which help to alleviate the restrictions of the basic radiosity solution.

Ray tracing algorithms can be modified to handle the intricacies of accurate light transport between surfaces without explicit form factor calculation.

"Intelligent" pre-processing of environments can subdivide the surfaces of an environment based on the geometry of the environment and on the probable location of light-shadow boundaries, creating an optimal subdivision.

As noted previously, the inherent diffuse nature of the basic radiosity algorithm has been relaxed with the development of multiple pass algorithms which incorporate both the diffuse and specular components of light.

Current research efforts include more accurate modeling of the characteristics of lights and surfaces, through BRDFs (bidirectional reflectance distribution functions), concentration on minimizing the cost of form factor calculation, and increasing the accuracy of form factor calculation.

## Slide 20 : Consolation Room Image.

This image suggests one treatment of a consolation room in a hospital or physician's office. It is part of a research experiment comparing the effect of different lighting on the overall appearance and perception of an environment.

Last changed April 01, 1998, G. Scott Owen, owen@siggraph.org