“Feature matching and deformation for texture synthesis” by Wu and Yu
Conference:
Type(s):
Title:
- Feature matching and deformation for texture synthesis
Presenter(s)/Author(s):
Abstract:
One significant problem in patch-based texture synthesis is the presence of broken features at the boundary of adjacent patches. The reason is that optimization schemes for patch merging may fail when neighborhood search cannot find satisfactory candidates in the sample texture because of an inaccurate similarity measure. In this paper, we consider both curvilinear features and their deformation. We develop a novel algorithm to perform feature matching and alignment by measuring structural similarity. Our technique extracts a feature map from the sample texture, and produces both a new feature map and texture map. Texture synthesis guided by feature maps can significantly reduce the number of feature discontinuities and related artifacts, and gives rise to satisfactory results.
References:
1. ASHIKHMIN, M. 2001. Synthesizing natural textures. In ACM Symposium on Interactive 3D Graphics, 217–226. Google ScholarDigital Library
2. BARROW, H., TENENBAUM, J., BOLLES, R., AND WOLF, H. 1977. Parametric correspondence and chamfer matching: Two new techniques for image matching. In Proc. 5th Intl. Joint Conf. on Art. Intell., 659–663.Google Scholar
3. BORGEFORS, G. 1988. Hierarchical chamfer matching: a parametric edge matching algorithm. IEEE Trans. Pattern Analysis and Machine Intelligence 10, 849–865. Google ScholarDigital Library
4. CANNY, J. 1986. A computational approach to edge detection. IEEE Trans. Pat. Anal. Mach. Intell. 8, 6, 679–698. Google ScholarDigital Library
5. EFROS, A., AND FREEMAN, W. 2001. Image quilting for texture synthesis and transfer. In SIGGRAPH’01, 341–346. Google ScholarDigital Library
6. EFROS, A., AND LEUNG, T. 1999. Texture synthesis by non-parametric sampling. In Intl. Conf. Computer Vision, 1033–1038. Google ScholarDigital Library
7. HERTZMANN, A., JACOBS, C., OLIVER, N., CURLESS, B., AND SALESIN, D. 2001. Image analogies. In SIGGRAPH’01, 327–340. Google ScholarDigital Library
8. HOSCHEK, J., AND LASSER, D. 1993. Fundamentals of Computer Aided Geometric Design. AK Peters, Ltd. Google ScholarDigital Library
9. KWATRA, V., SCHOOL, A., ESSA, I., TURK, G., AND BOBICK, A. 2003. Graphcut textures: Image and video synthesis using graph cuts. In SIGGRAPH’03, 277–286. Google ScholarDigital Library
10. LIANG, L., LIU, C., XU, Y., GUO, B., AND SHUM, H.-Y. 2001. Real-time texture synthesis using patch-based sampling. ACM Trans. Graphics 20, 3, 127–150. Google ScholarDigital Library
11. LIU, Y., AND LIN, W.-C. 2003. Deformable texture: the irregular-regular-irregular cycle. In The 3rd intl. workshop on texture analysis and synthesis, 65–70.Google Scholar
12. MEINGUET, J. 1979. Multivariate interpolation at arbitrary points made simple. J. Applied Math. Physics 5, 439–468.Google Scholar
13. PAVLIDIS, T. 1982. Algorithms for Graphics and Image Processing. Computer Science Press. Google ScholarDigital Library
14. SETHIAN, J. 1999. Level Set Methods and Fast Marching Methods. Cambridge University Press.Google Scholar
15. TOMASI, C., AND MANDUCHI, R. 1998. Bilateral filtering for gray and color images. In Proc. Intl. Conf. on Computer Vision, 836–846. Google ScholarDigital Library
16. TURK, G., AND O’BRIEN, J. 1999. Shape transformation using variational implicit functions. In SIGGRAPH 99 Conference Proceedings, 335–342. Google ScholarDigital Library
17. WEI, L.-Y., AND LEVOY, M. 2000. Fast texture synthesis using tree-structured vector quantization. In Proceedings of Siggraph, 479–488. Google ScholarDigital Library
18. ZHANG, J., ZHOU, K., VELHO, L., GUO, B., AND SHUM, H.-Y. 2003. Synthesis of progressively-variant textures on arbitrary surfaces. In SIGGRAPH’03, 295–302. Google ScholarDigital Library
19. ZITOVA, B., AND FLUSSER, J. 2003. Image registration methods: a survey. Image and Vision Computing 21, 977–1000.Google ScholarCross Ref