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Precomputed Local Radiance Transfer for Real-time Lighting Design Anders Wang Kristensen Tomas Akenine-Moller Henrik Wann Jensen SIGGRAPH ‘05 Presented by Shao-Ti Lee 2010/04/08 1
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Outline Introduction Related Work Constructing the Light Cloud Compressing Surface Radiance Real-time Relighting Results Conclusion 2
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Introduction Related Work Constructing the Light Cloud Compressing Surface Radiance Real-time Relighting Results Conclusion 3
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Introduction MAIN IDEA ◦ Unstructured light cloud. 4
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Introduction MAIN IDEA ◦ Unstructured light cloud. 5
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Introduction FEATURES ◦ Local, not distant illumination. Accurately represent incident radiance on different parts of the model. ◦ Light positions and intensities are changeable. ◦ Lights can be added or removed. ◦ Materials can be glossy. ◦ Camera is fully dynamic. ◦ Scene is assumed to be static. 6
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Introduction Related Work Constructing the Light Cloud Compressing Surface Radiance Real-time Relighting Results Conclusion 7
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Related Work Precompute the exitant radiance [Wood et al. 2000; Chen et al. 2002] ◦ Basis: sphere harmonics. 8
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Related Work Sphere harmonics. 9 Approximated Exitant Radiance Approximated Exitant Radiance in the SH basis SH Basis
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Related Work Clustered PCA(Principle Component Analysis) [Sloan et al. 2003] ◦ For geometry data representation compression. 10 Clustering Ex. K-Means PCA
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Introduction Related Work Constructing the Light Cloud Compressing Surface Radiance Real-time Relighting Results Conclusion 11
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Constructing the Light Cloud Before doing this, first divide the geometry into a set of discrete zones using a simple top-down partitioning algorithm. 12
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Constructing the Light Cloud Use a two-stage approach to construct the light cloud. ◦ Stage 1 Make a sufficiently dense uniform sampling of the region of interest. ◦ Stage 2 The light cloud is then simplified by clustering similar lights using a bottom-up clustering algorithm. 13
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Constructing the Light Cloud 14 This is for point lights.
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Constructing the Light Cloud 15 This is for diffuse surface.
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Constructing the Light Cloud 16 AC DEF GHI ABCDEFGHI Cluster List Priority queue sorted by △ jk △ AB △ AD △ BD △ CE ….. S S Compute △ SC, △ SD, △ SE, △ SF, △ SG, △ SH, △ SI and re-sort the priority queue to end a loop and stop until △ jk ≧ 1 for all j, k B
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Introduction Related Work Constructing the Light Cloud Compressing Surface Radiance Real-time Relighting Results Conclusion 17
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Compressing Surface Radiance Before compression ◦ Per vertex matrix X, with n p = n b x n l elements per color channel. n b : The number of SH bases. n l : The number of lights. After compression using CPCA 18 Cluster Mean PCA vectors (bases) weights
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Introduction Related Work Constructing the Light Cloud Compressing Surface Radiance Real-time Relighting Results Conclusion 19
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Real-time Relighting Organize the local lights in a kd-tree and locate the m nearest lights. 20
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Real-time Relighting To avoid undesirable popping effects, set the weight for each pre-computed local light to After computing all weights, normalization is used. And all weights are multiplied by the power of the light at l. 21
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Real-time Relighting Visibility problem 22 Solution: Use ray tracing with a few rays. Cannot assign weights!
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Real-time Relighting Discontinuity Problem 23 Suddenly disappear/appear due to occlusion! Solution: Smoothly fade out/in lights over time, but that now have become obscured by geometry.
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Real-time Relighting Computing Exitant Radiance For each cluster, x m and b i are constant. 24
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Real-time Relighting Reconstruct the vector of SH coefficients representing exitant radiance in a vertex program by evaluating ◦ Where is the variable to ensure that we get correct blending at the borders between clusters and between zones. ◦ Recall that 25
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Introduction Related Work Constructing the Light Cloud Compressing Surface Radiance Real-time Relighting Results Conclusion 26
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Results 27
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Results 28
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Results 29 Left: Method of authors. Right: Ray tracing with per pixel lighting.
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Results 30
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Introduction Related Work Constructing the Light Cloud Compressing Surface Radiance Real-time Relighting Results Conclusion 31
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Conclusion The system handles indirect illumination efficiently for models with more than 100,000 triangles. Future Work ◦ Soft shadow ◦ Spotlight 32
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