Generating Radiosity Maps on the GPU
MetadataShow full item record
Global illumination algorithms are used to render photorealistic images of 3D scenes taking into account both direct lighting from the light source and light reflected from other surfaces in the scene. Algorithms based on computing radiosity were among the first to be used to calculate indirect lighting, although they make assumptions that work only for diffusely reflecting surfaces. The classic radiosity approach divides a scene into multiple patches and generates a linear system of equations which, when solved, gives the values for the radiosity leaving each patch. This process can require extensive calculations and is therefore very slow. An alternative to solving a large system of equations is to use a Monte Carlo method of random sampling. In this approach, a large number of rays are shot from each patch into its surroundings and the irradiance values obtained from these rays are averaged to obtain a close approximation to the real value. <br /><br /> This thesis proposes the use of a Monte Carlo method to generate radiosity texture maps on graphics hardware. By storing the radiosity values in textures, they are immediately available for rendering, making this algorithm useful for interactive implementations. We have built a framework to run this algorithm and using current graphics cards (NV6800 or higher) it is possible to execute it almost interactively for simple scenes and within relatively low times for more complex scenes.
Cite this version of the work
Gabriel Moreno-Fortuny (2005). Generating Radiosity Maps on the GPU. UWSpace. http://hdl.handle.net/10012/1081