Examples for limitations of previous importance sampling methods. Previous methods produce significant noise in regions with highfrequency visibility variations due to complex occlusion or fine scene structures, such as the coffee mug handle very close to the popcorn box in LUNCH and the thin handrails in CONSTRUCTION. Insets show detailed comparisons for parts of the scenes rendered with different methods given the same amount of time (200 seconds for LUNCH and 500 seconds for CONSTRUCTION). The insets, from top to bottom, are Bidirectional Importance Sampling (BIS) [Wang and Akerlund 2009], Importance Caching (IC) [Georgiev et al. 2012], and our approach. Our method provides better noise reduction across the whole image including these difficult areas.
Abstract
This paper proposes the VisibilityCluster algorithm for efficient visibility approximation and representation in many-light
rendering. By carefully clustering lights and shading points, we can construct a visibility matrix that exhibits good local structures due to
visibility coherence of nearby lights and shading points. Average visibility can be efficiently estimated by exploiting the sparse structure
of the matrix and shooting only few shadow rays between clusters. Moreover, we can use the estimated average visibility as a quality
measure for visibility estimation, enabling us to locally refine VisibilityClusters with large visibility variance for improving accuracy. We
demonstrate that, with the proposed method, visibility can be incorporated into importance sampling at a reasonable cost for the manylight
problem, significantly reducing variance in Monte Carlo rendering. In addition, the proposed method can be used to increase
realism of local shading by adding directional occlusion effects. Experiments show that the proposed technique outperforms state-ofthe-
art importance sampling algorithms, and successfully enhances the preview quality for lighting design.
Publication
Yu-Ting Wu, Yung-Yu Chuang.
VisibilityCluster: Average Directional Visibility for Many-Light Rendering.
IEEE Transactions on Visualization and Computer Graphics (TVCG), volume 19, number 9, page 1566-1578, September 2013. BibTeX
TVCG 2013 paper (4.0MB PDF)
Digital library
Supplemental
Web interactive comparison
Last Update: May 2021