“Proxy Tracing: Unbiased Reciprocal Estimation for Optimized Sampling in BDPT”
Conference:
Type(s):
Title:
- Proxy Tracing: Unbiased Reciprocal Estimation for Optimized Sampling in BDPT
Presenter(s)/Author(s):
Abstract:
We present a novel path sampling technique using path substitution to greatly enhance BDPT’s performance in handling specular or highly glossy involved paths. We introduce a novel reciprocal estimator along with an efficiency-optimized setting. This estimator is more efficient and practically applicable, making it feasible for various sampling applications.
References:
[1]
Sai Bangaru, Tzu-Mao Li, and Fr?do Durand. 2020. Unbiased Warped-Area Sampling for Differentiable Rendering. ACM Trans. Graph. 39, 6 (2020), 245:1–245:18.
[2]
Jose H. Blanchet, Nan Chen, and Peter W. Glynn. 2015. Unbiased Monte Carlo computation of smooth functions of expectations via Taylor expansions. In 2015 Winter Simulation Conference (WSC). 360–367.
[3]
Thomas E. Booth. 2007. Unbiased Monte Carlo Estimation of the Reciprocal of an Integral. Nuclear Science and Engineering 156, 3 (2007), 403–407. arXiv:https://doi.org/10.13182/NSE07-A2707
[4]
Walt Disney Animation Studios Brent Burley. 2012. Physically-based shading at disney. In ACM SIGGRAPH. 1–27.
[5]
D. Chandler. 1987. Introduction To Modern Statistical. Introduction To Modern Statistical.
[6]
T. Davidovi?, J. Krivanek, M. Ha?an, and P. Slusallek. 2014. Progressive Light Transport Simulation on the GPU. ACM Trans. Graph. (TOG) 33, 3 (05 2014), 29:1–19.
[7]
X. Deng, S. Jiao, B. Bitterli, and W. Jarosz. 2019. Photon surfaces for robust, unbiased volumetric density estimation. ACM Trans. Graph. (TOG) 38, 4 (07 2019), 46:1–12.
[8]
I. Georgiev, J. Krivanek, T. Davidovivc, and P. Slusallek. 2012. Light Transport Simulation with Vertex Connection and Merging. ACM Trans. Graph. (TOG) 31, 6 (11 2012), 192:1–192:10.
[9]
Toshiya Hachisuka and Henrik Wann Jensen. 2009. Stochastic progressive photon mapping. ACM Transactions on Graphics (TOG) 28, 5 (2009), 141.
[10]
T. Hachisuka, S. Ogaki, and H. W. Jensen. 2008. Progressive Photon Mapping. ACM Trans. Graph. (TOG) 27 (12 2008), 130.
[11]
T. Hachisuka, J. Pantaleoni, and H. W. Jensen. 2012. A Path Space Extension for Robust Light Transport Simulation. ACM Trans. Graph. (TOG) 31, 6 (11 2012), 191:1–10.
[12]
Johannes Hanika, Marc Droske, and Luca Fascione. 2015. Manifold Next Event Estimation. Comput. Graph. Forum 34, 4 (07 2015), 87–97.
[13]
H. W. Jensen. 1996. Importance Driven Path Tracing Using the Photon Map. Eurographics Rendering Workshop (09 1996), 326–335.
[14]
H. W. Jensen and N. Christensen. 1995. Photon Maps in Bidirectional Monte Carlo Ray Tracing of Complex Objects. Computers & Graphics 19 (03 1995), 215–224.
[15]
Ivo Kondapaneni, Petr V?voda, Pascal Grittmann, Tom?? Sk?ivan, Philipp Slusallek, and Jaroslav K?iv?nek. 2019. Optimal multiple importance sampling. ACM Transactions on Graphics (TOG) 38, 4 (2019), 1–14.
[16]
E. P. Lafortune and Y. D. Willems. 1999. A 5D Tree to Reduce the Variance of Monte Carlo Ray Tracing. In Rendering Techniques.
[17]
He Li, Beibei Wang, Changhe Tu, Kun Xu, Nicolas Holzschuch, and Ling-Qi Yan. 2022. Unbiased Caustics Rendering Guided by Representative Specular Paths. In SIGGRAPH Asia 2022 Conference Papers. 1–8.
[18]
Zehui Lin, Chenxiao Hu, Jinzhu Jia, and Sheng Li. 2023. Hypothesis Testing for Progressive Kernel Estimation and VCM Framework. IEEE Transactions on Visualization and Computer Graphics (2023), 1–15.
[19]
Z. Lin, S. Li, X. Zeng, C. Zhang, J. Jia, G. Wang, and D. Manocha. 2020. CPPM: chi-squared progressive photon mapping. ACM Trans. Graph. (TOG) 39, 6 (11 2020), 240:1–12.
[20]
T. M?ller, M. Gross, and J. Nov?k. 2017. Practical Path Guiding for Efficient Light-Transport Simulation. Computer Graphics Forum 36, 4 (07 2017), 91–100.
[21]
K. Nabata, K. Iwasaki, and Y. Dobashi. 2020. Resampling-aware Weighting Functions for Bidirectional Path Tracing Using Multiple Light Sub-Paths. ACM Trans. Graph. (TOG) 39, 2 (03 2020), 15:1–11.
[22]
Jan Nov?k, Iliyan Georgiev, Johannes Hanika, and Wojciech Jarosz. 2018. Monte Carlo methods for volumetric light transport simulation. Computer Graphics Forum (Proceedings of Eurographics – State of the Art Reports) 37, 2 (May 2018).
[23]
S. G. Parker, J. Bigler, A. Dietrich, H. Friedrich, J. Hoberock, D. Luebke, D. McAllister, M. McGuire, K. Morley, A. Robison, et al. 2010. Optix: a general purpose ray tracing engine. ACM Trans. Graph. (TOG) 29, 4 (07 2010), 66:1–13.
[24]
S. Popov, R. Ramamoorthi, F. Durand, and G. Drettakis. 2015. Probabilistic Connections for Bidirectional Path Tracing. Computer Graphics Forum 34, 4 (07 2015), 75–86.
[25]
Hao Qin, Xin Sun, Qiming Hou, Baining Guo, and Kun Zhou. 2015. Unbiased Photon Gathering for Light Transport Simulation. ACM Trans. Graph. 34, 6, Article 208 (nov 2015), 14 pages.
[26]
A. Rath, P. Grittmann, Sebastian H., P. V?voda, P. Slusallek, and J. K?iv?nek. 2020. Variance-Aware Path Guiding. ACM Trans. Graph. (TOG) 39, 4 (07 2020), 151:1–12.
[27]
Alexander Rath, Pascal Grittmann, Sebastian Herholz, Philippe Weier, and Philipp Slusallek. 2022a. EARS: Efficiency-Aware Russian Roulette and Splitting. ACM Trans. Graph. (TOG) 41, 4, Article 81 (jul 2022), 14 pages.
[28]
Alexander Rath, Pascal Grittmann, Sebastian Herholz, Philippe Weier, and Philipp Slusallek. 2022b. EARS: Efficiency-Aware Russian Roulette and Splitting. ACM Transactions on Graphics (Proceedings of SIGGRAPH 2022) 41, 4, Article 81 (jul 2022), 14 pages.
[29]
F. Su, S. Li, and G. Wang. 2022. SPCBPT: Subspace-based Probabilistic Connections for Bidirectional Path Tracing. ACM Trans. Graph. (TOG) 41, 4 (07 2022), 77:1–14.
[30]
Y. Tokuyoshi and T. Harada. 2018. Bidirectional path tracing using backward stochastic light culling. 1–2.
[31]
Y. Tokuyoshi and T. Harada. 2019. Hierarchical russian roulette for vertex connections. ACM Trans. Graph. (TOG) 38, 4 (07 2019), 36:1–12.
[32]
Eric Veach. 1998. Robust monte carlo methods for light transport simulation. Ph. D. Dissertation. Stanford, CA, USA. Advisor(s) Guibas, Leonidas J. AAI9837162.
[33]
E. Veach and L. Guibas. 1995a. Bidirectional estimators for light transport. In Photorealistic Rendering Techniques. 145–167.
[34]
E. Veach and L. Guibas. 1995b. Optimally Combining Sampling Techniques for Monte Carlo Rendering. In Proceedings of the 22nd Annual Conference on Computer Graphics and Interactive Techniques. 419–428.
[35]
J. Vorba, O. Karl?k, M. ?ik, T. Ritschel, and J. Krivanek. 2014. On-line Learning of Parametric Mixture Models for Light Transport Simulation. ACM Trans. Graph. (TOG) 33, 4 (07 2014), 101:1–11.
[36]
Rex West, Iliyan Georgiev, Adrien Gruson, and Toshiya Hachisuka. 2020. Continuous Multiple Importance Sampling. ACM Trans. Graph. 39, 4, Article 136 (aug 2020), 12 pages.
[37]
Rex West, Iliyan Georgiev, and Toshiya Hachisuka. 2022. Marginal Multiple Importance Sampling. In SIGGRAPH Asia 2022 Conference Papers (SA ’22). Association for Computing Machinery, New York, NY, USA, Article 42, 8 pages.
[38]
Shanhe Wu. 2008. Some improvements of Acz?l’s inequality and Popoviciu’s inequality. Computers & Mathematics with Applications 56, 5 (2008), 1196–1205.
[39]
M Zackary, B Benedikt, G Iliyan, and J Wojciech. 2022. Unbiased and consistent rendering using biased estimators. ACM Trans. Graph. (TOG) 41, 4 (7 2022), 48:1–13.
[40]
Tizian Zeltner, Iliyan Georgiev, and Wenzel Jakob. 2020. Specular Manifold Sampling for Rendering High-Frequency Caustics and Glints. Transactions on Graphics (Proceedings of SIGGRAPH) 39, 4 (July 2020).
