Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1145/1964921.1964938acmconferencesArticle/Chapter ViewAbstractPublication PagessiggraphConference Proceedingsconference-collections
research-article

Illumination decomposition for material recoloring with consistent interreflections

Published: 25 July 2011 Publication History

Abstract

Changing the color of an object is a basic image editing operation, but a high quality result must also preserve natural shading. A common approach is to first compute reflectance and illumination intrinsic images. Reflectances can then be edited independently, and recomposed with the illumination. However, manipulating only the reflectance color does not account for diffuse interreflections, and can result in inconsistent shading in the edited image. We propose an approach for further decomposing illumination into direct lighting, and indirect diffuse illumination from each material. This decomposition allows us to change indirect illumination from an individual material independently, so it matches the modified reflectance color. To address the underconstrained problem of decomposing illumination into multiple components, we take advantage of its smooth nature, as well as user-provided constraints. We demonstrate our approach on a number of examples, where we consistently edit material colors and the associated interreflections.

Supplementary Material

Supplemental material. (a43-carroll.zip)
MP4 File (tp016_11.mp4)

References

[1]
Bai, J., Chandraker, M., Ng, T.-T., and Ramamoorthi, R. 2010. A dual theory of inverse and forward light transport. In ECCV '10, 294--307.
[2]
Barrow, H., and Tenenbaum, J. 1978. Recovering intrinsic scene characteristics from images. Computer Vision Systems 27, 9, 3--26.
[3]
Bioucas-Dias, J. M., and Figueiredo, M. A. T. 2007. A new twist: Two-step iterative shrinkage/thresholding algorithms for image restoration. IEEE Trans. on Image Processing 16, 12 (dec.), 2992--3004.
[4]
Bousseau, A., Paris, S., and Durand, F. 2009. User-assisted intrinsic images. ACM Trans. Graph. 28, 130:1--130:10.
[5]
Candes, E., Romberg, J., and Tao, T. 2006. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Trans. Inform. Theory 52, 2, 489--509.
[6]
Chuang, Y.-Y., Curless, B., Salesin, D. H., and Szeliski, R. 2001. A bayesian approach to digital matting. In CVPR '01, vol. 2, 264--271.
[7]
Cohen, M. F., and Wallace, J. 1993. Radiosity and realistic image synthesis. Academic Press Professional, Inc., San Diego, CA.
[8]
Donoho, D. 2006. Compressed sensing. IEEE Trans. on Inform. Theory 52, 4, 1289--1306.
[9]
Fang, H., and Hart, J. C. 2004. Textureshop: texture synthesis as a photograph editing tool. ACM Trans. Graph. 23, 354--359.
[10]
Fattal, R., Carroll, R., and Agrawala, M. 2009. Edge-based image coarsening. ACM Trans. Graph. 29, 6:1--6:11.
[11]
Fattal, R. 2008. Single image dehazing. ACM Trans. Graph. 27, 72:1--72:9.
[12]
Finlayson, G., Hordley, S., Lu, C., and Drew, M. 2006. On the removal of shadows from images. IEEE Trans. PAMI 28, 1, 59--68.
[13]
Gutierrez, D., Seron, F. J., Lopez-Moreno, J., Sanchez, M. P., Fandos, J., and Reinhard, E. 2008. Depicting procedural caustics in single images. ACM Trans. Graph. 27, 120:1--120:9.
[14]
Hašan, M., Pellacini, F., and Bala, K. 2006. Direct-to-indirect transfer for cinematic relighting. ACM Trans. Graph. 25, 1089--1097.
[15]
Holland, P. W., and Welsch, R. E. 1977. Robust regression using iteratively reweighted least-squares. Communications in Statistics - Theory and Methods 6 (September), 813--827.
[16]
Horn, B. K. P. 1986. Robot Vision. The MIT Press, March.
[17]
Hsu, E., Mertens, T., Paris, S., Avidan, S., and Durand, F. 2008. Light mixture estimation for spatially varying white balance. ACM Trans. Graph. 27, 70:1--70:7.
[18]
Joshi, N., Zitnick, C., Szeliski, R., and Kriegman, D. 2009. Image deblurring and denoising using color priors. In CVPR '09., 1550--1557.
[19]
Keller, A. 1997. Instant radiosity. In Proc. SIGGRAPH, 49--56.
[20]
Khan, E. A., Reinhard, E., Fleming, R. W., and Bülthoff, H. H. 2006. Image-based material editing. ACM Trans. Graph. 25, 654--663.
[21]
Kopf, J., Cohen, M. F., Lischinski, D., and Uyttendaele, M. 2007. Joint bilateral upsampling. ACM Trans. Graph. 26.
[22]
Land, E. H., John, and Mccann, J. 1971. Lightness and retinex theory. Journal of the Optical Society of America, 1--11.
[23]
Levin, A., and Weiss, Y. 2007. User assisted separation of reflections from a single image using a sparsity prior. IEEE Trans. PAMI 29, 9, 1647--1654.
[24]
Levin, A., Fergus, R., Durand, F., and Freeman, W. T. 2007. Image and depth from a conventional camera with a coded aperture. ACM Trans. Graph. 26.
[25]
Levin, A., Lischinski, D., and Weiss, Y. 2008. A closed-form solution to natural image matting. IEEE Trans. PAMI 30 (February), 228--242.
[26]
Mohan, A., Tumblin, J., and Choudhury, P. 2007. Editing soft shadows in a digital photograph. IEEE Comput. Graph. Appl. 27 (March), 23--31.
[27]
Nayar, S. K., Krishnan, G., Grossberg, M. D., and Raskar, R. 2006. Fast separation of direct and global components of a scene using high frequency illumination. ACM Trans. Graph. 25, 935--944.
[28]
Obert, J., Křivánek, J., Sýkora, D., and Pattanaik, S. 2007. Interactive light transport editing for flexible global illumination. In ACM SIGGRAPH 2007 sketches.
[29]
Oh, B. M., Chen, M., Dorsey, J., and Durand, F. 2001. Image-based modeling and photo editing. In Proc. SIGGRAPH, 433--442.
[30]
Pharr, M., and Humphreys, G. 2004. Physically Based Rendering: From Theory to Implementation. Morgan Kaufmann.
[31]
Ramamoorthi, R., and Hanrahan, P. 2001. A signal-processing framework for inverse rendering. In Proc. SIGGRAPH, 117--128.
[32]
Rudin, L. I., Osher, S., and Fatemi, E. 1992. Nonlinear total variation based noise removal algorithms. Phys. D 60 (November), 259--268.
[33]
Schoeneman, C., Dorsey, J., Smits, B., Arvo, J., and Greenberg, D. 1993. Painting with light. In Proc. SIGGRAPH, 143--146.
[34]
Seitz, S., Matsushita, Y., and Kutulakos, K. 2005. A theory of inverse light transport. In ICCV '05, vol. 2, 1440--1447.
[35]
Shen, L., Tan, P., and Lin, S. 2008. Intrinsic image decomposition with non-local texture cues. In CVPR '08., 1--7.
[36]
Shor, Y., and Lischinski, D. 2008. The shadow meets the mask: Pyramid-based shadow removal. Comput. Graph. Forum 27, 2, 577--586.
[37]
Sinha, P., and Adelson, E. 1993. Recovering reflectance and illumination in a world of painted polyhedra. In ICCV '93, 156--163.
[38]
Tappen, M. F., Russell, B. C., and Freeman, W. T. 2003. Exploiting the sparse derivative prior for super-resolution and image demosaicing. In IEEE Workshop on Stat. and Comput. Theories of Vision.
[39]
Tappen, M. F., Freeman, W. T., and Adelson, E. H. 2005. Recovering intrinsic images from a single image. IEEE Trans. PAMI 27, 9, 1459--1472.
[40]
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, 1098--1107.
[41]
Wang, J., and Cohen, M. 2007. Optimized color sampling for robust matting. In CVPR '07., 1--8.
[42]
Weiss, Y. 2001. Deriving intrinsic images from image sequences. In ICCV '01, vol. 2, 68--75.

Cited By

View all
  • (2024)Depth-based adaptable image layer prediction using bidirectional depth semantic fusionThe Visual Computer10.1007/s00371-024-03430-240:10(7045-7055)Online publication date: 28-May-2024
  • (2023)PaletteNeRF: Palette-based Appearance Editing of Neural Radiance Fields2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52729.2023.01982(20691-20700)Online publication date: Jun-2023
  • (2021)Planar Abstraction and Inverse Rendering of 3D Indoor EnvironmentsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2019.296077627:6(2992-3006)Online publication date: 1-Jun-2021
  • Show More Cited By

Index Terms

  1. Illumination decomposition for material recoloring with consistent interreflections

    Recommendations

    Comments

    Please enable JavaScript to view thecomments powered by Disqus.

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    SIGGRAPH '11: ACM SIGGRAPH 2011 papers
    August 2011
    869 pages
    ISBN:9781450309431
    DOI:10.1145/1964921
    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 ACM 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]

    Sponsors

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 25 July 2011

    Permissions

    Request permissions for this article.

    Check for updates

    Qualifiers

    • Research-article

    Funding Sources

    Conference

    SIGGRAPH '11
    Sponsor:

    Acceptance Rates

    SIGGRAPH '11 Paper Acceptance Rate 82 of 432 submissions, 19%;
    Overall Acceptance Rate 1,822 of 8,601 submissions, 21%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)10
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 24 Sep 2024

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Depth-based adaptable image layer prediction using bidirectional depth semantic fusionThe Visual Computer10.1007/s00371-024-03430-240:10(7045-7055)Online publication date: 28-May-2024
    • (2023)PaletteNeRF: Palette-based Appearance Editing of Neural Radiance Fields2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52729.2023.01982(20691-20700)Online publication date: Jun-2023
    • (2021)Planar Abstraction and Inverse Rendering of 3D Indoor EnvironmentsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2019.296077627:6(2992-3006)Online publication date: 1-Jun-2021
    • (2021)SmartShadow: Artistic Shadow Drawing Tool for Line Drawings2021 IEEE/CVF International Conference on Computer Vision (ICCV)10.1109/ICCV48922.2021.00534(5371-5380)Online publication date: Oct-2021
    • (2021)ShadingNet: Image Intrinsics by Fine-Grained Shading DecompositionInternational Journal of Computer Vision10.1007/s11263-021-01477-5Online publication date: 27-May-2021
    • (2021)Inverse Light TransportComputer Vision10.1007/978-3-030-03243-2_803-1(1-3)Online publication date: 9-Feb-2021
    • (2020)Erasing Appearance Preservation in Optimization-Based SmoothingComputer Vision – ECCV 202010.1007/978-3-030-58539-6_4(55-70)Online publication date: 7-Nov-2020
    • (2018)LIME: Live Intrinsic Material Estimation2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition10.1109/CVPR.2018.00661(6315-6324)Online publication date: Jun-2018
    • (2018)Interreflections in Computer VisionJournal of Mathematical Imaging and Vision10.1007/s10851-017-0781-x60:5(661-680)Online publication date: 28-Dec-2018
    • (2018)Efficient spectral reconstruction using a trichromatic camera via sample optimizationThe Visual Computer10.1007/s00371-017-1469-334:12(1773-1783)Online publication date: 12-Jan-2018
    • Show More Cited By

    View Options

    Get Access

    Login options

    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