Updated: Oct 28, 2010

Unbiased, Adaptive Stochastic Sampling for Rendering Inhomogeneous Participating Media  

Yonghao Yue, Kei Iwasaki, Bing-Yu Chen, Yoshinori Dobashi, and Tomoyuki Nishita

The University of Tokyo     Wakayama University     National Taiwan University     Hokkaido University      The University of Tokyo

Realistic rendering of participating media is one of the major subjects in computer graphics. Monte Carlo techniques are widely used for realistic rendering because they provide unbiased solutions, which converge to exact solutions. Methods based on Monte Carlo techniques generate a number of light paths, each of which consists of a set of randomly selected scattering events. Finding a new scattering event requires free path sampling to determine the distance from the previous scattering event, and is usually a timeconsuming process for inhomogeneous participating media. To address this problem, we propose an adaptive and unbiased sampling technique using kd-tree based space partitioning. A key contribution of our method is an automatic scheme that partitions the spatial domain into sub-spaces (partitions) based on a cost model that evaluates the expected sampling cost. The magnitude of performance gain obtained by our method becomes larger for more inhomogeneous media, and rises to two orders compared to traditional free path sampling techniques.


Participating media, free path sampling, space partitioning, Monte Carlo technique, unbiased

ACM Transactions on Graphics (Proc. SIGGRAPH Asia 2010) Vol.29, No.6, pp.177:1-7

Paper: PDF(9.7MB)
Video: sky.mp4(41MB)