“Texture Mixing and Texture Movie Synthesis using Statistical Learning” by Bar-Joseph, El-Yaniv, Lischinski and Werman

  • ©Ziv Bar-Joseph, Ran El-Yaniv, Daniel (Dani) Lischinski, and Michael Werman

Conference:


Type:


Interest Area:


    Application

Title:

    Texture Mixing and Texture Movie Synthesis using Statistical Learning

Session/Category Title:   Texturing

Presenter(s)/Author(s):


Abstract:


    An algorithm based on statistical learning for synthesizing static and time-varying textures that match the appearance of an input texture. The algorithm is general and automatic.

References:


    1. Bar-Joseph, Z., Lischinski, D., Werman, M., Dubnov, M., & El-Yaniv, R. (1999). Granular synthesis of sound textures using statistical learning. ICMC 99 Conference Proceedings.
    2. De Bonet, J. S. (1997). Multiresolution sampling procedure for analysis and synthesis of texture images. ACM SIGGRAPH 97 Conference Proceedings, 361-368.
    3. De Bonet, J.S., & Viola, P. (1997). A non-parametric multi-scale statistical model for natural images. Advances in Neural Information Processing, 10.
    4. Heeger, D. J. & Bergen, J. R. (1995). Pyramid-based texture analysis/synthesis. ACM SIGGRAPH 95 Conference Proceedings, 229-238.
    5. Zhu, S. C., Wu, Y., & Mumford, D. (1998). Filters, random fields and maximum entropy (frame) – towards a unified theory for texture modeling. International Journal of Computer Vision, 27 (2), 107-126.

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