“LazyFluids: appearance transfer for fluid animations”

  • ©Ondřej Jamriška, Jakub Fišer, Paul Asente, Jingwan Lu, Eli Shechtman, and Daniel Sýkora

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Title:

    LazyFluids: appearance transfer for fluid animations

Session/Category Title:   Transfer & Capture

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Abstract:


    In this paper we present a novel approach to appearance transfer for fluid animations based on flow-guided texture synthesis. In contrast to common practice where pre-captured sets of fluid elements are combined in order to achieve desired motion and look, we bring the possibility of fine-tuning motion properties in advance using CG techniques, and then transferring the desired look from a selected appearance exemplar. We demonstrate that such a practical work-flow cannot be simply implemented using current state-of-the-art techniques, analyze what the main obstacles are, and propose a solution to resolve them. In addition, we extend the algorithm to allow for synthesis with rich boundary effects and video exemplars. Finally, we present numerous results that demonstrate the versatility of the proposed approach.

References:


    1. Bargteil, A. W., Sin, F., Michaels, J. E., Goktekin, T., and O’Brien, J. F. 2006. A texture synthesis method for liquid animations. In Proceedings of ACM SIGGRAPH/Eurographics Symposium on Computer Animation, 345–351. Google ScholarDigital Library
    2. Barnes, C., Shechtman, E., Finkelstein, A., and Goldman, D. B. 2009. PatchMatch: A randomized correspondence algorithm for structural image editing. ACM Transactions on Graphics 28, 3, 24. Google ScholarDigital Library
    3. Barnes, C., Shechtman, E., Goldman, D. B., and Finkelstein, A. 2010. The generalized PatchMatch correspondence algorithm. In Proceedings of European Conference on Computer Vision, 29–43. Google ScholarDigital Library
    4. Bénard, P., Cole, F., Kass, M., Mordatch, I., Hegarty, J., Senn, M. S., Fleischer, K., Pesare, D., and Breeden, K. 2013. Stylizing animation by example. ACM Transactions on Graphics 32, 4, 119. Google ScholarDigital Library
    5. Bhat, K. S., Seitz, S. M., Hodgins, J. K., and Khosla, P. K. 2004. Flow-based video synthesis and editing. ACM Transactions on Graphics 23, 3, 360–363. Google ScholarDigital Library
    6. Bousseau, A., Neyret, F., Thollot, J., and Salesin, D. 2007. Video watercolorization using bidirectional texture advection. ACM Transactions on Graphics 26, 3, 104. Google ScholarDigital Library
    7. Browning, M., Barnes, C., Ritter, S., and Finkelstein, A. 2014. Stylized keyframe animation of fluid simulations. In Proceedings of the Workshop on Non-Photorealistic Animation and Rendering, 63–70. Google ScholarDigital Library
    8. Chen, J., and Wang, B. 2010. High quality solid texture synthesis using position and index histogram matching. The Visual Computer 26, 4, 253–262. Google ScholarDigital Library
    9. Darabi, S., Shechtman, E., Barnes, C., Goldman, D. B., and Sen, P. 2012. Image melding: Combining inconsistent images using patch-based synthesis. ACM Transactions on Graphics 31, 4, 82. Google ScholarDigital Library
    10. Han, J., Zhou, K., Wei, L.-Y., Gong, M., Bao, H., Zhang, X., and Guo, B. 2006. Fast example-based surface texture synthesis via discrete optimization. The Visual Computer 22, 9–11, 918–925. Google ScholarDigital Library
    11. Hertzmann, A., Jacobs, C. E., Oliver, N., Curless, B., and Salesin, D. H. 2001. Image analogies. In Proceedings of SIGGRAPH 2001, 327–340. Google ScholarDigital Library
    12. Kaspar, A., Neubert, B., Lischinski, D., Pauly, M., and Kopf, J. 2015. Self tuning texture optimization. Computer Graphics Forum 34, 2, 349–360.Google ScholarDigital Library
    13. Kopf, J., Fu, C.-W., Cohen-Or, D., Deussen, O., Lischinski, D., and Wong, T.-T. 2007. Solid texture synthesis from 2d exemplars. ACM Transactions on Graphics 26, 3, 2. Google ScholarDigital Library
    14. Kwatra, V., Schödl, A., Essa, I. A., Turk, G., and Bobick, A. F. 2003. Graphcut textures: Image and video synthesis using graph cuts. ACM Transactions on Graphics 22, 3, 277–286. Google ScholarDigital Library
    15. Kwatra, V., Essa, I. A., Bobick, A. F., and Kwatra, N. 2005. Texture optimization for example-based synthesis. ACM Transactions on Graphics 24, 3, 795–802. Google ScholarDigital Library
    16. Kwatra, V., Adalsteinsson, D., Kim, T., Kwatra, N., Carlson, M., and Lin, M. C. 2007. Texturing fluids. IEEE Transactions on Visualization and Computer Graphics 13, 5, 939–952. Google ScholarDigital Library
    17. Lefebvre, S., and Hoppe, H. 2006. Appearance-space texture synthesis. ACM Transactions on Graphics 25, 3, 541–548. Google ScholarDigital Library
    18. Liao, Z., Joshi, N., and Hoppe, H. 2013. Automated video looping with progressive dynamism. ACM Transactions on Graphics 32, 4, 77. Google ScholarDigital Library
    19. Lukáč, M., Fišer, J., Bazin, J.-C., Jamriška, O., Sorkine-Hornung, A., and Sýkora, D. 2013. Painting by feature: Texture boundaries for example-based image creation. ACM Transaction on Graphics 32, 4, 116. Google ScholarDigital Library
    20. Max, N., Crawfis, R., and Williams, D. 1992. Visualizing wind velocities by advecting cloud textures. In Proceedings of IEEE Conference on Visualization, 179–183. Google ScholarDigital Library
    21. Narain, R., Kwatra, V., Lee, H.-P., Kim, T., Carlson, M., and Lin, M. C. 2007. Feature-guided dynamic texture synthesis on continuous flows. In Proceedings of Eurographics Symposium on Rendering, 361–370. Google ScholarDigital Library
    22. Newson, A., Almansa, A., Fradet, M., Gousseau, Y., and Pérez, P. 2014. Video inpainting of complex scenes. SIAM Journal of Imaging Science 7, 4, 1993–2019.Google ScholarCross Ref
    23. Neyret, F. 2003. Advected textures. In Proceedings of ACM SIGGRAPH/Eurographics Symposium on Computer Animation, 147–153. Google ScholarDigital Library
    24. Perlin, K. 1985. An image synthesizer. SIGGRAPH Comput. Graph. 19, 3, 287–296. Google ScholarDigital Library
    25. Reeves, W. T. 1983. Particle systems—a technique for modeling a class of fuzzy objects. ACM Transactions on Graphics 2, 2, 91–108. Google ScholarDigital Library
    26. Rosenberger, A., Cohen-Or, D., and Lischinski, D. 2009. Layered shape synthesis: Automatic generation of control maps for non-stationary textures. ACM Transactions on Graphics 28, 5, 107. Google ScholarDigital Library
    27. Schödl, A., Szeliski, R., Salesin, D. H., and Essa, I. 2000. Video textures. In SIGGRAPH Conference Proceedings, 489–498. Google ScholarDigital Library
    28. Shechtman, E., Rav-Acha, A., Irani, M., and Seitz, S. M. 2010. Regenerative morphing. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 615–622.Google Scholar
    29. Simakov, D., Caspi, Y., Shechtman, E., and Irani, M. 2008. Summarizing visual data using bidirectional similarity. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Google Scholar
    30. Stam, J. 1999. Stable fluids. In SIGGRAPH Conference Proceedings, 121–128. Google ScholarDigital Library
    31. Wei, L.-Y., Han, J., Zhou, K., Bao, H., Guo, B., and Shum, H.-Y. 2008. Inverse texture synthesis. ACM Transactions on Graphics 27, 3. Google ScholarDigital Library
    32. Wexler, Y., Shechtman, E., and Irani, M. 2007. Space-time completion of video. IEEE Transactions on Pattern Analysis and Machine Intelligence 29, 3, 463–476. Google ScholarDigital Library
    33. Yu, Q., Neyret, F., Bruneton, E., and Holzschuch, N. 2011. Lagrangian texture advection: Preserving both spectrum and velocity field. IEEE Transactions on Visualization and Computer Graphics 17, 11, 1612–1623. Google ScholarDigital Library

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