2 research outputs found

    A Parallel Radiosity System for Large Data Sets

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    this paper we will explore this definition and define a practical working system. Most radiosity methods use a discretisation approach, in which the environment is divided into a finite set of patches. This approach was initially used in thermal engineering and applied to diffuse reflection by Goral et al [6]. The radiance function of each surface is approximated by the set of patches attributed to that surface. More recent methods have used polynomials [15] and wavelet models [7] to represent the radiance functions over surfaces. The CARM system is patch-based, with each patch holding a mesh of sample points. Although discretised systems have a number of shortcomings (such as aliasing) they can accurately represent very abrupt changes in the radiance function. The input geometry to the system is triangulated; this allows all object primitives and also all complex objects to be represented by meshes. The input triangles are then automatically tested for D0 discontinuities (i.e. tests for intersecting or abutting triangles) and also for excessive size, and automatically subdivided if required. The triangles left after such subdivision correspond to a traditional hand-crafted radiosity patches. Radiance values (or flux values) are stored at sample points, which are located at patch vertices, and also within the patch. These sample points are stored in a mesh, which can be triangulated and then interpolated to reconstruct the radiance function. By adaptive subdivision of the mesh the system allows sample points to be added as the solution progresses, When new sample points are added the mesh is re-triangulated; these triangles are analogous to traditional elements. Subdivision is controlled by examining the gradient and difference between neighbouring sample points; if e..
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