Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
research-article

Adaptive matrix column sampling and completion for rendering participating media

Published: 05 December 2016 Publication History

Abstract

Several scalable many-light rendering methods have been proposed recently for the efficient computation of global illumination. However, gathering contributions of virtual lights in participating media remains an inefficient and time-consuming task. In this paper, we present a novel sparse sampling and reconstruction method to accelerate the gathering step of the many-light rendering for participating media. Our technique explores the observation that the scattered lightings are usually locally coherent and of low rank even in heterogeneous media. In particular, we first introduce a matrix formation with light segments as columns and eye ray segments as rows, and formulate the gathering step into a matrix sampling and reconstruction problem. We then propose an adaptive matrix column sampling and completion algorithm to efficiently reconstruct the matrix by only sampling a small number of elements. Experimental results show that our approach greatly improves the performance, and obtains up to one order of magnitude speedup compared with other state-of-the-art methods of many-light rendering for participating media.

Supplementary Material

ZIP File (a167-huo.zip)
Supplemental file.

References

[1]
Candès, E., and Recht, B. 2009. Exact matrix completion via convex optimization. Found. Comput. Math. 9, 6 (Dec.), 717--772.
[2]
Chandrasekhar, S. 1960. Radiative transfer. Courier Corporation.
[3]
Dachsbacher, C., Křivánek, J., Hašan, M., Arbree, A., Walter, B., and Novák, J. 2014. Scalable realistic rendering with many-light methods. In Computer Graphics Forum, vol. 33, Wiley Online Library, 88--104.
[4]
Engelhardt, T., Novk, J., Schmidt, T., and Dachsbacher, C. 2012. Approximate bias compensation for rendering scenes with heterogeneous participating media. In Computer Graphics Forum, 2145--2154.
[5]
Frederickx, R., Bartels, P., and Dutré, P. 2015. Adaptive lightslice for virtual ray lights. In EUROGRAPHICS 2015-Short Papers, The Eurographics Association, 61--64.
[6]
Georgiev, I., and Slusallek, P. 2010. Simple and robust iterative importance sampling of virtual point lights. In In Eurographics short papers.
[7]
Georgiev, I., Křivánek, J., Popov, S., and Slusallek, P. 2012. Importance caching for complex illumination. Computer Graphics Forum 31, 2. EUROGRAPHICS 2012.
[8]
Georgiev, I., Krivanek, J., Hachisuka, T., Nowrouzezahrai, D., and Jarosz, W. 2013. Joint importance sampling of low-order volumetric scattering. ACM Trans. Graph. 32, 6, 164--1.
[9]
Gkioulekas, I., Xiao, B., Zhao, S., Adelson, E. H., Zickler, T., and Bala, K. 2013. Understanding the role of phase function in translucent appearance. ACM Transactions on Graphics (TOG) 32, 5, 147.
[10]
Gkioulekas, I., Zhao, S., Bala, K., Zickler, T., and Levin, A. 2013. Inverse volume rendering with material dictionaries. Acm Transactions on Graphics 32, 6, 1210--1214.
[11]
Hachisuka, T., Jarosz, W., Weistroffer, R. P., Dale, K., Humphreys, G., Zwicker, M., and Jensen, H. W. 2008. Multidimensional adaptive sampling and reconstruction for ray tracing. In ACM Transactions on Graphics (TOG), vol. 27, ACM, 33.
[12]
Hašan, M., Pellacini, F., and Bala, K. 2007. Matrix row-column sampling for the many-light problem. ACM Trans. Graph. 26, 3, 26:1--10.
[13]
Huang, F.-C., and Ramamoorthi, R. 2010. Sparsely precomputing the light transport matrix for real-time rendering. In Computer Graphics Forum, vol. 29, Wiley Online Library, 1335--1345.
[14]
Huo, Y., Wang, R., Jin, S., Liu, X., and Bao, H. 2015. A matrix sampling-and-recovery approach for many-lights rendering. ACM Trans. Graph. 34, 6 (Oct.), 210:1--210:12.
[15]
Jakob, W., 2010. Mitsuba renderer. http://www.mitsuba-renderer.org.
[16]
Jarosz, W., Nowrouzezahrai, D., Sadeghi, I., and Jensen, H. W. 2011. A comprehensive theory of volumetric radiance estimation using photon points and beams. ACM Transactions on Graphics (TOG) 30, 1, 5.
[17]
Jarosz, W., Nowrouzezahrai, D., Thomas, R., Sloan, P.P., and Zwicker, M. 2011. Progressive photon beams. ACM Transactions on Graphics (TOG) 30, 6, 181.
[18]
Keller, A. 1997. Instant radiosity. In Proc. SIGGRAPH '97, 49--56.
[19]
Krishnamurthy, A., and Singh, A. 2014. On the power of adaptivity in matrix completion and approximation. Eprint Arxiv.
[20]
Krivánek, J., Georgiev, I., Hachisuka, T., Vévoda, P., Sik, M., Nowrouzezahrai, D., and Jarosz, W. 2014. Unifying points, beams, and paths in volumetric light transport simulation. ACM Trans. Graph. 33, 4, 103--1.
[21]
Lafortune, E., and Willems, Y. 1996. Rendering participating media with bidirecitonal path tracing. In Eurographics Workshop on Rendering, 91--100.
[22]
LaSalle, D., and Karypis, G. 2013. Multi-threaded graph partitioning. In Parallel & Distributed Processing (IPDPS), 2013 IEEE 27th International Symposium on, IEEE, 225--236.
[23]
Mitchell, D. P. 1987. Generating antialiased images at low sampling densities. In ACM SIGGRAPH Computer Graphics, vol. 21, ACM, 65--72.
[24]
Novák, J., Nowrouzezahrai, D., Dachsbacher, C., and Jarosz, W. 2012. Progressive virtual beam lights. In Computer Graphics Forum, vol. 31, Wiley Online Library, 1407--1413.
[25]
Novák, J., Nowrouzezahrai, D., Dachsbacher, C., and Jarosz, W. 2012. Virtual ray lights for rendering scenes with participating media. ACM Trans. Graph. 31, 4, 60:1--60:11.
[26]
Ou, J., and Pellacini, F. 2011. Lightslice: matrix slice sampling for the many-lights problem. ACM Trans. Graph. 30, 6 (Dec.), 179:1--179:8.
[27]
Peers, P., Mahajan, D. K., Lamond, B., Ghosh, A., Matusik, W., Ramamoorthi, R., and Debevec, P. 2009. Compressive light transport sensing. ACM Transactions on Graphics (TOG) 28, 1, 3.
[28]
Pegoraro, V. 2009. Efficient physically-based simulation of light transport in participating media. University of Utah.
[29]
Raab, M., Seibert, D., and Keller, A. 2008. Unbiased global illumination with participating media. In Monte Carlo and Quasi-Monte Carlo Methods 2006. Springer, 591--605.
[30]
Ren, P., Wang, J., Gong, M., Lin, S., Tong, X., and Guo, B. 2013. Global illumination with radiance regression functions. ACM Transactions on Graphics (TOG) 32, 4, 130.
[31]
Sen, P., Zwicker, M., Rousselle, F., Yoon, S.-E., and Kalantari, N. K. 2015. Denoising your monte carlo renders: recent advances in image-space adaptive sampling and reconstruction. In ACM SIGGRAPH 2015 Courses, ACM, 11.
[32]
Walter, B., Fernandez, S., Arbree, A., Bala, K., Donikian, M., and Greenberg, D. P. 2005. Lightcuts: a scalable approach to illumination. ACM Trans. Graph. 24, 3, 1098--1107.
[33]
Walter, B., Arbree, A., Bala, K., and Greenberg, D. P. 2006. Multidimensional lightcuts. In ACM Transactions on Graphics (TOG), vol. 25, ACM, 1081--1088.
[34]
Walter, B., Khungurn, P., and Bala, K. 2012. Bidirectional lightcuts. ACM Trans. Graph. 31, 4 (July), 59:1--59:11.
[35]
Wang, J., Dong, Y., Tong, X., Lin, Z., and Guo, B. 2009. Kernel nyström method for light transport. In ACM Transactions on Graphics (TOG), vol. 28, ACM, 29.
[36]
Zwicker, M., Jarosz, W., Lehtinen, J., Moon, B., Ramamoorthi, R., Rousselle, F., Sen, P., Soler, C., and Yoon, S.-E. 2015. Recent advances in adaptive sampling and reconstruction for monte carlo rendering. In Computer Graphics Forum, vol. 34, Wiley Online Library, 667--681.

Cited By

View all

Index Terms

  1. Adaptive matrix column sampling and completion for rendering participating media

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Transactions on Graphics
    ACM Transactions on Graphics  Volume 35, Issue 6
    November 2016
    1045 pages
    ISSN:0730-0301
    EISSN:1557-7368
    DOI:10.1145/2980179
    Issue’s Table of Contents
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 05 December 2016
    Published in TOG Volume 35, Issue 6

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. adaptive rendering
    2. many-light rendering
    3. matrix completion
    4. participating media

    Qualifiers

    • Research-article

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)12
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 02 Sep 2024

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)High-Performance Many-Light RenderingEncyclopedia of Computer Graphics and Games10.1007/978-3-031-23161-2_397(865-870)Online publication date: 5-Jan-2024
    • (2022)PowerNet: Learning-Based Real-Time Power-Budget RenderingIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.306436728:10(3486-3498)Online publication date: 1-Oct-2022
    • (2021)Real-time indirect illumination by virtual planar area lightsComputers & Graphics10.1016/j.cag.2021.04.022Online publication date: Apr-2021
    • (2021)High-Performance Many-Light RenderingEncyclopedia of Computer Graphics and Games10.1007/978-3-319-08234-9_397-1(1-6)Online publication date: 20-Jan-2021
    • (2020)An Approach to Global Illumination Calculation Based on Hybrid Cone TracingIEEE Access10.1109/ACCESS.2020.2994597(1-1)Online publication date: 2020
    • (2019)Scalable Virtual Ray Lights Rendering for Participating MediaComputer Graphics Forum10.1111/cgf.1377038:4(57-65)Online publication date: 30-Jul-2019
    • (2018)Adaptive Sampling for GPU-based 3-D Volume RenderingProceedings of the 2nd International Symposium on Image Computing and Digital Medicine10.1145/3285996.3286002(27-31)Online publication date: 13-Oct-2018
    • (2018)Monte Carlo Methods for Volumetric Light Transport SimulationComputer Graphics Forum10.1111/cgf.1338337:2(551-576)Online publication date: 22-May-2018
    • (2017)Lighting grid hierarchy for self-illuminating explosionsACM Transactions on Graphics10.1145/3072959.307360436:4(1-10)Online publication date: 20-Jul-2017

    View Options

    Get Access

    Login options

    Full Access

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media