“AppProp: all-pairs appearance-space edit propagation” by An and Pellacini

  • ©Xiaobo An and Fabio Pellacini

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Title:

    AppProp: all-pairs appearance-space edit propagation

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Abstract:


    We present an intuitive and efficient method for editing the appearance of complex spatially-varying datasets, such as images and measured materials. In our framework, users specify rough adjustments that are refined interactively by enforcing the policy that similar edits are applied to spatially-close regions of similar appearance. Rather than proposing a specific user interface, our method allows artists to quickly and imprecisely specify the initial edits with any method or workflow they feel most comfortable with. An energy optimization formulation is used to propagate the initial rough adjustments to the final refined ones by enforcing the editing policy over all pairs of points in the dataset. We show that this formulation is equivalent to solving a large linear system defined by a dense matrix. We derive an approximate algorithm to compute such a solution interactively by taking advantage of the inherent structure of the matrix. We demonstrate our approach by editing images, HDR radiance maps, and measured materials. Finally, we show that our framework generalizes prior methods while providing significant improvements in generality, robustness and efficiency.

References:


    1. Adobe Systems Inc, 2007. Photoshop CS 3.Google Scholar
    2. Chen, J., Paris, S., and Durand, F. 2007. Real-time edgeaware image processing with the bilateral grid. ACM Transactions on Graphics 26, 3 (July), 103:1–103:9. Google ScholarDigital Library
    3. Drineas, P., and Mahoney, M. W. 2005. On the nystrom method for approximating a gram matrix for improved kernelbased learning. J. Mach. Learn. Res. 6, 2153–2175. Google ScholarDigital Library
    4. Eisemann, E., and Durand, F. 2004. Flash photography enhancement via intrinsic relighting. ACM Transactions on Graphics 23, 3, 673–678. Google ScholarDigital Library
    5. Fowlkes, C., Belongie, S., and Malik, J. 2001. Efficient spatiotemporal grouping using the nyström method. In CVPR 2001, 231–238.Google Scholar
    6. Fowlkes, C., Belongie, S., Chung, F., and Malik, J. 2004. Spectral grouping using the nyström method. In IEEE Transactions on PAMI, vol. 26, 214–215. Google ScholarDigital Library
    7. Golub, G., and Van Loan, C. 1996. Matrix Computations. The Johns Hopkins University Press.Google Scholar
    8. Gu, J., Tu, C.-I., Ramamoorthi, R., Belhumeur, P., Matusik, W., and Nayar, S. 2006. Time-varying surface appearance: acquisition, modeling and rendering. ACM Transactions on Graphics 25, 3, 762–771. Google ScholarDigital Library
    9. Hašan, M., Pellacini, F., and Bala, K. 2007. Matrix row-column sampling for the many-light problem. ACM Transactions on Graphics 26, 3, 26:1–26:10. Google ScholarDigital Library
    10. Irony, R., Cohen-Or, D., and Lischinski, D. 2005. Colorization by example. In Rendering Techniques 2005, 201–210. Google ScholarCross Ref
    11. Kopf, J., Cohen, M. F., Lischinski, D., and Uyttendaele, M. 2007. Joint bilateral upsampling. ACM Transactions on Graphics 26, 3, 96:1–96:5. Google ScholarDigital Library
    12. Lawrence, J., Ben-Artzi, A., DeCoro, C., Matusik, W., Pfister, H., Ramamoorthi, R., and Rusinkiewicz, S. 2006. Inverse shade trees for non-parametric material representation and editing. ACM Transactions on Graphics 25, 3, 735–745. Google ScholarDigital Library
    13. Lensch, H. P. A., Kautz, J., Goesele, M., Heidrich, W., and Seidel, H.-P. 2003. Image-based reconstruction of spatial appearance and geometric detail. ACM Transactions on Graphics 22, 2, 234–257. Google ScholarDigital Library
    14. Levin, A., Lischinski, D., and Weiss, Y. 2004. Colorization using optimization. ACM Transactions on Graphics 23, 3, 689–694. Google ScholarDigital Library
    15. Lischinski, D., Farbman, Z., Uyttendaele, M., and Szeliski, R. 2006. Interactive local adjustment of tonal values. ACM Transactions on Graphics 25, 3, 646–653. Google ScholarDigital Library
    16. Luan, Q., Wen, F., Cohen-Or, D., Liang, L., Xu, Y., and Shum, H. 2007. Natural image colorization. In Rendering Techniques 2007. Google ScholarCross Ref
    17. Marschner, S. R., Westin, S. H., Arbree, A., and Moon, J. T. 2005. Measuring and modeling the appearance of finished wood. ACM Transactions on Graphics 24, 3 (Aug.), 727–734. Google ScholarDigital Library
    18. Pellacini, F., and Lawrence, J. 2007. Appwand: Editing measured materials using appearance-driven optimization. ACM Transactions on Graphics 26, 3, 54:1–54:9. Google ScholarDigital Library
    19. Petschnigg, G., Szeliski, R., Agrawala, M., Cohen, M., Hoppe, H., and Toyama, K. 2004. Digital photography with flash and no-flash image pairs. ACM Transactions on Graphics 23, 3, 664–672. Google ScholarDigital Library
    20. Qu, Y., Wong, T.-T., and Heng, P.-A. 2006. Manga colorization. ACM Transactions on Graphics 25, 3, 1214–1220. Google ScholarDigital Library
    21. Reinhard, E., Ward, G., Pattanaik, S., and Debevec, P. 2005. High Dynamic Range Imaging. Morgan Kaufmann.Google Scholar
    22. Wang, J., Agrawala, M., and Cohen, M. F. 2007. Soft scissors: An interactive tool for realtime high quality matting. ACM Transactions on Graphics 26, 3, 9:1–9:6. Google ScholarDigital Library
    23. Williams, C., and Seeger, M. 2000. Using the nystrom method to speed up kernel machines. In Advances in Neural Information Processing Systems, vol. 13, 682–688.Google Scholar


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