Global Illumination Using Well-Separated Pair Decomposition

نویسندگان

Norbert Bus

Nabil H. Mustafa

Venceslas Biri

چکیده

Instant radiosity methods rely on using a large number of virtual point lights (VPLs) to approximate global illumination. Efficiency considerations require grouping the VPLs into a small number of clusters that are treated as individual lights with respect to each point to be shaded. Two examples of clustering algorithms are Lightcuts [WFA∗05] and LightSlice [OP11]. In this work we use the notion of geometric separatedness of point sets as a basis for a data structure for pre-computing and compactly storing a set of candidate VPL clusterings. Our data structure is created prior to rendering, is view-independent and relies only on geometric and radiometric information. For any point to be shaded, we show that a suitable clustering of the VPLs can be efficiently extracted from this data structure. We develop the above framework into an accurate and efficient clustering algorithm based on well-separated pair decompositions which outperforms earlier work in speed and/or quality for diffuse scenes.

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Bibliography of Literature

[3] P. B. Callahan, " Optimal parallel all-nearest-neighbors using the well-separated pair decomposition, " in

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INDEX TERMS: none.

Well-separated pair decomposition, introduced by Callahan and Kosaraju [3], has found numerous applications in solving proximity problems for points in the Euclidean space. A pair of point sets (A, B) is c-well-separated if the distance between A,B is at least c times the diameters of both A and B. A well-separated pair decomposition of a point set consists of a set of well-separated pairs that...

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