Vladimir G. Kim
Skip Abstract Section
Skip Supplemental Material SectionAbstract
This article presents a framework for symmetry-guided texture synthesis and processing. It is motivated by the long-standing problem of how to optimize, transfer, and control the spatial patterns in textures. The key idea is that symmetry representations that measure autocorrelations with respect to all transformations of a group are a natural way to describe spatial patterns in many real-world textures. To leverage this idea, we provide methods to transfer symmetry representations from one texture to another, process the symmetries of a texture, and optimize textures with respect to properties of their symmetry representations. These methods are automatic and robust, as they don't require explicit detection of discrete symmetries. Applications are investigated for optimizing, processing, and transferring symmetries and textures.
Supplemental Material
- 100KR. 2012. http://www.flickr.com/photos/100kr/209708058/.Google Scholar
- Bar-Joseph, Z., El-Yaniv, R., Lischinski, D., and Werman, M. 2001. Texture mixing and texture movie synthesis using statistical learning. IEEE Trans. Vis. Comput. Graph. 7, 2, 120--135. Google ScholarDigital Library
- Bonneh, Y., Reisfeld, D., and Yeshurun, Y. 1994. Quantification of local symmetry: Application to texture discrimination. Spatial Vis. 8, 4, 515--530.Google ScholarCross Ref
- Brennan, D. 2012. http://www.flickr.com/photos/davidbrennan/251080600/.Google Scholar
- Chetverikov, D. 1995. Pattern orientation and texture symmetry. Comput. Anal. Images Patterns 970. Google ScholarDigital Library
- Cwazymandy. 2012. http://www.flickr.com/photos/cwazymandy/3938576605/.Google Scholar
- Database, C. N. 2012. http://vivid.cse.psu.edu/texturedb/gallery/.Google Scholar
- Dolescum. 2012. http://www.flickr.com/photos/dolescum/4399058804/.Google Scholar
- Ebert, D. S., Musgrave, F. K., Peachey, D., Perlin, K., and Worley, S. 2002. Texturing and Modeling: A Procedural Approach. Morgan Kaufmann. Google ScholarDigital Library
- Efros, A. A. and Freeman, W. T. 2001. Image quilting for texture synthesis and transfer. In Proceedings of the SIGGRAPH'01 Conference. Google ScholarDigital Library
- Efros, A. A. and Leung, T. K. 1999. Texture synthesis by nonparametric sampling. In Proceedings of the International IEEE Conference on Computer Vision (ICCV'99). Google ScholarDigital Library
- Euart. 2012. http://www.flickr.com/photos/euart/282152062/.Google Scholar
- Golovinskiy, A., Podolak, J., and Funkhouser, T. 2009. Symmetry-aware mesh processing. In Proceedings of the Mathematics of Surfaces Conference. Google ScholarDigital Library
- Hays, J. H., Leordeanu, M., Efros, A. A., and Liu, Y. 2006. Discovering texture regularity as a higher-order correspondence problem. In Proceedings of the European Conference on Computer Vision. Google ScholarDigital Library
- Heeger, D. J. and Bergen, J. R. 1995. Pyramid-Based texture analysis/synthesis. In Proceedings of the SIGGRAPH'95 Conference. Google ScholarDigital Library
- Heigan, M. 2012. http://www.flickr.com/photos/martin_heigan/2352361336/.Google Scholar
- Hertzmann, A., Jacobs, C. E., Oliver, N., Curless, B., and Salesin, D. H. 2001. Image analogies. In Proceedings of the SIGGRAPH'01 Conference. Google ScholarDigital Library
- Igarashi, T., Moscovich, T., and Hughes, J. F. 2005. As-Rigid-As-Possible shape manipulation. ACM Trans. Graph. 24, 3. Google ScholarDigital Library
- Kazhdan, M., Chazelle, B., Dobkin, D., Finkelstein, A., and Funkhouser, T. 2002. A reflective symmetry descriptor. In Proceedings of the European Conference on Computer Vision (ECCV'02). Google ScholarDigital Library
- Kazhdan, M., Chazelle, B., Dobkin, D., Funkhouser, T., and Rusinkiewicz, S. 2003. A reflective symmetry descriptor for 3D models. Algorithmica. Google ScholarDigital Library
- Kazhdan, M., Funkhouser, T., and Rusinkiewicz, S. 2004. Symmetry descriptors and 3D shape matching. In Proceedings of the Symposium on Geometry Processing (SGP'04). Google ScholarDigital Library
- Kelly, M. F. and Levine, M. D. 1995. Annular symmetry operators: A method for locating and describing objects. In Proceedings of the International Conference on Computer Vision (ICCV'95). Google ScholarDigital Library
- Kwatra, V., Essa, I., Bobick, A., and Kwatra, N. 2005. Texture optimization for example-based synthesis. In Proceedings of the SIGGRAPH'05 Conference. Google ScholarDigital Library
- Kwatra, V., Schödl, A., Essa, I., Turk, G., and Bobick, A. 2003. Graphcut textures: Image and video synthesis using graph cuts. In Proceedings of the SIGGRAPH'03 Conference. Google ScholarDigital Library
- Leung, T. and Malik, J. 1996. Detecting localizing and grouping repeated scene elements from an image. In Proceedings of the European Conference on Computer Vision (ECCV'96). Google ScholarDigital Library
- Lewis, C. 2012. http://www.flickr.com/photos/cloois/17435429/.Google Scholar
- Liu, Y., Lin, W.-C., and Hays, J. H. 2004. Near regular texture analysis and manipulation. ACM Trans. Graph. 23, 1. Google ScholarDigital Library
- Matusik, W., Zwicker, M., and Durand, F. 2005. Texture design using a simplicial complex of morphable textures. In Proceedings of the SIGGRAPH'05 Conference. Google ScholarDigital Library
- Mitra, N. J., Guibas, L., and Pauly, M. 2007. Symmetrization. In Proceedings of the SIGGRAPH'07 Conference. Google ScholarDigital Library
- Park, M., Brocklehurst, K., Collins, R. T., and Liu, Y. 2009. Deformed lattice detection in real-world images using mean-shift belief propagation. IEEE Trans. Pattern Anal. Mach. Intell. Google ScholarDigital Library
- Pauly, M., Mitra, N. J., Wallner, J., Pottmann, H., and Guibas, L. 2008. Discovering structural regularity in 3D geometry. ACM Trans. Graph. 27. Google ScholarDigital Library
- Perivolaris, J. 2012. http://www.flickr.com/photos/dr_john2005/211195030/.Google Scholar
- Podolak, J., Shilane, P., Golovinskiy, A., Rusinkiewicz, S., and Funkhouser, T. 2006. A planar-reflective symmetry transform for 3D shapes. In Proceedings of the SIGGRAPH'06 Conference. Google ScholarDigital Library
- Portilla, J. and Simoncelli, E. P. 2000. A parametric texture model based on joint statistics of complex wavelet coefficients. Int. J. Comput. Vis. Google ScholarDigital Library
- Reisfeld, D., Wolfson, H., and Yeshurun, Y. 1995. Context-Free attentional operators: The generalized symmetry transform. Int. J. Comput. Vis. Google ScholarDigital Library
- Shallowend24401. 2012. http://www.flickr.com/photos/shallowend24401/295133809/.Google Scholar
- Snappa2006. 2012. http://www.flickr.com/photos/snappa2006/2106318872/.Google Scholar
- Tsai, R. Y. 1986. An efficient and accurate camera calibration technique for 3D machine vision. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR'86).Google Scholar
- Turina, A., Tuytelaars, T., and Gool, L. V. 2001. Efficient grouping under perspective skew. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR'01).Google Scholar
- Wei, L.-Y., Lefebvre, S., Kwatra, V., and Turk, G. 2009. State of the art in example-based texture synthesis. Eurographics State of the Art report.Google Scholar
- Wei, L.-Y. and Levoy, M. 2000. Fast texture synthesis using tree-structured vector quantization. In Proceedings of the SIGGRAPH'00 Conference. Google ScholarDigital Library
- Xu, K., Cohne-Or, D., Ju, T., Liu, L., Zhang, H., Zhou, S., and Xiong, Y. 2009. Feature-Aligned shape texturing. In Proceedings of the SIGGRAPH'09 Asia Conference. Google ScholarDigital Library
- Zabrodsky, H., Peleg, S., and Avnir, D. 1995. Symmetry as a continuous feature. IEEE Trans. Pattern Anal. Mach. Intell. 17, 12. Google ScholarDigital Library
Index Terms
Symmetry-guided texture synthesis and manipulation
Recommendations
Periodic pattern of texture analysis and synthesis based on texels distribution
Recently, sample-based texture synthesis techniques have drawn significant attention from researchers. These existing approaches mainly use the Markov Random Field (MRF) or texture features as texture model to analyze the local properties of sample ...
Perspective-aware texture analysis and synthesis
This paper presents a novel texture synthesis scheme for anisotropic 2D textures based on perspective feature analysis and energy optimization. Given an example texture, the synthesis process starts with analyzing the texel (TEXture ELement) scale ...
An evolutionary system for near-regular texture synthesis
Near-regular texture is probably among the most difficult to handle in the texture synthesis area, because the synthesis must preserve the holistic structural property and the local randomness simultaneously. In this paper, motivated by the relationship ...
Comments