“Appearance-space texture synthesis” by Lefebvre and Hoppe

  • ©Sylvain Lefebvre and Hugues Hoppe

Conference:


Type:


Title:

    Appearance-space texture synthesis

Presenter(s)/Author(s):



Abstract:


    The traditional approach in texture synthesis is to compare color neighborhoods with those of an exemplar. We show that quality is greatly improved if pointwise colors are replaced by appearance vectors that incorporate nonlocal information such as feature and radiance-transfer data. We perform dimensionality reduction on these vectors prior to synthesis, to create a new appearance-space exemplar. Unlike a texton space, our appearance space is low-dimensional and Euclidean. Synthesis in this information-rich space lets us reduce runtime neighborhood vectors from 5×5 grids to just 4 locations. Building on this unifying framework, we introduce novel techniques for coherent anisometric synthesis, surface texture synthesis directly in an ordinary atlas, and texture advection. Remarkably, we achieve all these functionalities in real-time, or 3 to 4 orders of magnitude faster than prior work.

References:


    1. Ashikhmin, M. 2001. Synthesizing natural textures. Symposium on Interactive 3D Graphics, 217–226.]] Google ScholarDigital Library
    2. De Bonet, J. 1997. Multiresolution sampling procedure for analysis and synthesis of texture images. ACM SIGGRAPH, 361–368.]] Google ScholarDigital Library
    3. Efros, A., and Leung, T. 1999. Texture synthesis by non-parametric sampling. ICCV, 1033–1038.]] Google ScholarDigital Library
    4. Garber, D. 1981. Computational models for texture analysis and texture synthesis. PhD Dissertation, University of Southern California.]] Google ScholarDigital Library
    5. Heeger, D., and Bergen, J. 1995. Pyramid-based texture analysis/synthesis. ACM SIGGRAPH, 229–238.]] Google ScholarDigital Library
    6. Hertzmann, A., Jacobs, C., Oliver, N., Curless, B., and Salesin, D. 2001. Image analogies. ACM SIGGRAPH, 327–340.]] Google ScholarDigital Library
    7. Hertzmann, A., and Zorin, D. 2000. Illustrating smooth surfaces. ACM SIGGRAPH, 517–526.]] Google ScholarDigital Library
    8. Kwatra, V., Essa, I., Bobick, A., and Kwatra, N. 2005. Texture optimization for example-based synthesis. SIGGRAPH, 795–802.]] Google ScholarDigital Library
    9. Lefebvre, S., and Hoppe, H. 2005. Parallel controllable texture synthesis. ACM SIGGRAPH, 777–786.]] Google ScholarDigital Library
    10. Leung, T., and Malik, J. 2001. Representing and recognizing the visual appearance of materials using 3D textons. IJCV 43(1), 29–44.]] Google ScholarDigital Library
    11. Liang, L., Liu, C., Xu, Y., Guo, B., and Shum, H.-Y. 2001. Real-time texture synthesis by patch-based sampling. ACM TOG 20(3), 127–150.]] Google ScholarDigital Library
    12. Magda, S., and Kriegman, D. 2003. Fast texture synthesis on arbitrary meshes. Eurographics Symposium on Rendering, 82–89.]] Google ScholarDigital Library
    13. Malik, J., Belongie, S., Shi, J., and Leung, T. 1999. Textons, contours and regions: Cue integration in image segmentation. ICCV, 918–925.]] Google ScholarDigital Library
    14. Neyret, F., and Cani, M.-P. 1999. Pattern-based texturing revisited. ACM SIGGRAPH, 235–242.]] Google ScholarDigital Library
    15. Neyret, F. 2003. Advected textures. Symposium on computer animation, 147–153.]] Google ScholarDigital Library
    16. Popat, K., and Picard, R. 1993. Novel cluster-based probability model for texture synthesis, classification, and compression. Visual Communications and Image Processing, 756–768.]]Google Scholar
    17. Portilla, J., and Simoncelli, E. 2000. A parametric texture model based on joint statistics of complex wavelet coefficients. IJCV (40) 1.]] Google ScholarDigital Library
    18. Praun, E., Finkelstein, A., and Hoppe, H. 2000. Lapped textures. ACM SIGGRAPH, 465–470.]] Google ScholarDigital Library
    19. Roweis, S. 1997. EM algorithms for PCA and SPCA. NIPS, 626–632.]] Google ScholarDigital Library
    20. Roweis, S., and Saul, L. 2000. Nonlinear dimensionality reduction by locally linear embedding. Science, 290:2323–2326.]]Google ScholarCross Ref
    21. Sloan, P.-P., Liu, X., Shum, H.-Y., and Snyder, J. 2003. Bi-scale radiance transfer. ACM SIGGRAPH, 370–375.]] Google ScholarDigital Library
    22. Taponecco, F., and Alexa, M. 2004. Steerable texture synthesis. Eurographics Conference.]]Google Scholar
    23. Tenenbaum, J., De Silva, V., and Langford, J. 2000. A global geometric framework for nonlinear dimensionality reduction. Science, 290:2319–2323.]]Google ScholarCross Ref
    24. Tong, X., Zhang, J., Liu, L., Wang, X., Guo, B., and Shum, H.-Y. 2002. Synthesis of bidirectional texture functions on arbitrary surfaces. ACM SIGGRAPH, 665–672.]] Google ScholarDigital Library
    25. Turk, G. 2001. Texture synthesis on surfaces. SIGGRAPH, 347–354.]] Google ScholarDigital Library
    26. Wei, L.-Y., and Levoy, M. 2000. Fast texture synthesis using tree-structured vector quantization. ACM SIGGRAPH, 479–488.]] Google ScholarDigital Library
    27. Wei, L.-Y., and Levoy, M. 2001. Texture synthesis over arbitrary manifold surfaces. ACM SIGGRAPH, 355–360.]] Google ScholarDigital Library
    28. Wei, L.-Y., and Levoy, M. 2003. Order-independent texture synthesis. http://graphics.stanford.edu/papers/texture-synthesis-sig03/.]]Google Scholar
    29. Wu, Q., and Yu, Y. 2004. Feature matching and deformation for texture synthesis. ACM SIGGRAPH, 362–365.]] Google ScholarDigital Library
    30. Ying, L., Hertzmann, A., Biermann, H., and Zorin, D. 2001. Texture and shape synthesis on surfaces. Symposium on Rendering, 301–312.]] Google ScholarDigital Library
    31. Zhang, J., Zhou, K., Velho, L., Guo, B., and Shum, H.-Y. 2003. Synthesis of progressively-variant textures on arbitrary surfaces. ACM SIGGRAPH, 295–302.]] Google ScholarDigital Library


ACM Digital Library Publication: