Global Illumination Using Well-Separated Pair Decomposition

Abstract

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 Lightcutsi¾ź[WFA*05] and LightSlicei¾ź[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.