Fast algorithms for computing the largest empty rectangle
SCG '87 Proceedings of the third annual symposium on Computational geometry
SIGGRAPH '89 Proceedings of the 16th annual conference on Computer graphics and interactive techniques
Display of clouds taking into account multiple anisotropic scattering and sky light
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Rendering participating media with bidirectional path tracing
Proceedings of the eurographics workshop on Rendering techniques '96
Efficient simulation of light transport in scenes with participating media using photon maps
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Metropolis Light Transport for Participating Media
Proceedings of the Eurographics Workshop on Rendering Techniques 2000
Mining for empty spaces in large data sets
Theoretical Computer Science - Database theory
Robust monte carlo methods for light transport simulation
Robust monte carlo methods for light transport simulation
ACM SIGGRAPH ASIA 2009 Courses
Proceedings of the 2011 SIGGRAPH Asia Conference
Importance sampling of area lights in participating media
ACM SIGGRAPH 2011 Talks
Decoupled ray-marching of heterogeneous participating media
ACM SIGGRAPH 2011 Talks
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
State of the art in photon density estimation
ACM SIGGRAPH 2012 Courses
Importance Sampling Techniques for Path Tracing in Participating Media
Computer Graphics Forum
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
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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.