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Instant Radiosity Alexander Keller University Kaiserslautern Present by Li-Fong Lin
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Outline Global Illumination Quai-Monte Carlo Integration Algorithm Extensions Reasults
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Global Illumination Radiance equation : Shorthand : In the radiosity setting, restricted to only diffuse reflection :
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Global Illumination Detector functional Ψ: the sum of orthonormal base vectors of a finite vector space. Directly select the function below in this paper
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Global Illumination In realistic applications : ||T fr || < 1, less than 100% of the incident radiance is reflected. So the Neumann series converges and can be used to solve the integral equation.
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Quasi-Monte Carlo Integration Replace the random numbers used in standard Monte Carlo with low-discrepancy points. Much smoother convergence at a slightly superior rate. Halton sequence is used in this paper.
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van der Corput sequence
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Algorithm Approximate the radiance L in the radiosity setting by a discrete density of M point light sources. The particle approximation yields the very fast rendering algorithm: Li Pi y L(y)
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Algorithm Only small deviation from mean reflectivity in realistic scene models. We can use fractional absorption and avoid Russian Roulette absorption. ρN particles will survive after one reflection.
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Algorithm The Quasi-Random Walk –Evaluate T mn L e using N point lights, T mn T fd L e by using ρN point lights, and so on. –Finally the quasi-Monte Carlo integration is performed by accumulating all images with the weight 1/N
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Pseudo-Code
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Extensions Jittered Low Discrepancy Sampling
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Extensions Specular Effects –By a random decision each surface is tested to be specular or diffuse according to its BRDF. –Mirror the origin ray by the specular surface. Realtime Walkthroughs –In an animated environment, trace fixed length paths. –Keeping the last N images of the last N paths, the oldest image is replaced by the new one each time. –Render the global diffuse illumination (only direct illumination) into textures, then can be displayed interactively.
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Results
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