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Unbiased and Efficient Free Path Sampling Method

Thursday, October 11, 11AM – 12:30PM
POB 4.304

Yonghao Yue

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 time consuming 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.

Biography Yonghao Yue is an assistant professor at the Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, the University of Tokyo, Japan, since 2011. He is also an assistant professor at the Department of Information Science, School of Science, the University of Tokyo, Japan, since 2012. His research interests center on computer graphics, including realistic image synthesis, global illumination, Monte Carlo techniques and physically-based simulations.He received his B.S., M.S. and Ph.D. degrees in Computer Science from the University of Tokyo,Japan, in 2005, 2007 and 2011, respectively, under the supervision of Professor Tomoyuki Nishita.

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