Global Ray-Bundle Tracing with Hardware Acceleration

The paper presents a single-pass, view-dependent method to solve the general rendering equation, using a combined finite element and random walk approach. Applying finite element techniques, the surfaces are decomposed into planar patches that are assumed to have position independent, but not direction independent radiance. The direction dependent radiance function is then computed by random walk using bundles of parallel rays. In a single step of the walk, the radiance transfer is evaluated exploiting the hardware z-buffer of workstations, making the calculation fast. The proposed method is particularly efficient for scenes including not very specular materials illuminated by large area light-sources or sky-light. In order to increase the speed for difficult lighting situations, walks can be selected according to their importance. The importance can be explored adaptively by the Metropolis sampling method.

[1]  Harald Niederreiter,et al.  Random number generation and Quasi-Monte Carlo methods , 1992, CBMS-NSF regional conference series in applied mathematics.

[2]  Stephen H. Westin,et al.  A global illumination solution for general reflectance distributions , 1991, SIGGRAPH.

[3]  Peter Shirley,et al.  Discrepancy as a Quality Measure for Sample Distributions , 1991, Eurographics.

[4]  Peter Shirley,et al.  Monte Carlo techniques for direct lighting calculations , 1996, TOGS.

[5]  Donald P. Greenberg,et al.  A two-pass solution to the rendering equation: A synthesis of ray tracing and radiosity methods , 1987, SIGGRAPH.

[6]  A. Keller A Quasi-Monte Carlo Algorithm for the Global Illumination Problem in the Radiosity Setting , 1995 .

[7]  Donald P. Greenberg,et al.  A radiosity method for non-diffuse environments , 1986, SIGGRAPH.

[8]  I. M. Soboĺ,et al.  Die Monte-Carlo-Methode , 1971 .

[9]  Leonidas J. Guibas,et al.  Optimally combining sampling techniques for Monte Carlo rendering , 1995, SIGGRAPH.

[10]  Yves D. Willems,et al.  Bi-directional path tracing , 1993 .

[11]  Robert L. Cook,et al.  Distributed ray tracing , 1984, SIGGRAPH.

[12]  David Salesin,et al.  Clustering for glossy global illumination , 1997, TOGS.

[13]  David Salesin,et al.  Global illumination of glossy environments using wavelets and importance , 1996, TOGS.

[14]  Leonidas J. Guibas,et al.  Metropolis light transport , 1997, SIGGRAPH.

[15]  István Deák,et al.  Random Number Generators and Simulation , 1990 .

[16]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[17]  James T. Kajiya,et al.  The rendering equation , 1998 .

[18]  Mateu Sbert,et al.  Quasi Monte-Carlo and extended first shot improvements to the multi-path method , 1998 .

[19]  Leonidas J. Guibas,et al.  Bidirectional Estimators for Light Transport , 1995 .

[20]  Yves D. Willems,et al.  A 5D Tree to Reduce the Variance of Monte Carlo Ray Tracing , 1995, Rendering Techniques.

[21]  Eric P. Lafortune,et al.  Monte Carlo light tracing with direct computation of pixel intensities , 1993 .

[22]  H. Friedrich,et al.  Ermakow, S. M., Die Monte-Carlo-Methode und verwandte Fragen. 291 S., Berlin 1975. VEB Deutscher Verlag der Wissenschaften. M 62,- , 1976 .

[23]  Sumanta N. Pattanaik,et al.  Adjoint equations and random walks for illumination computation , 1995, TOGS.

[24]  Claude Puech,et al.  A general two-pass method integrating specular and diffuse reflection , 1989, SIGGRAPH '89.

[25]  Chris Buckalew,et al.  Fast Illumination Networks: Realistic Rendering with General Reflectance Functions , 1989 .

[26]  Martin E. Newell,et al.  A new approach to the shaded picture problem , 1972 .