Shugo Yamaguchi
ABSTRACT
In this paper, we present a novel method for creating a painted image from a photograph using an existing painting as a style source. The core idea is to identify the corresponding objects in the two images in order to select patches more appropriately. We automatically make a region correspondence between the painted source image and the target photograph by computing color and texture feature distances. Next, we conduct a patch-based synthesis that preserves the appropriate source and target features. Unlike previous example-based approaches of painting style transfer, our results successfully reflect the features of the source images even if the input images have various colors and textures. Our method allows us to automatically render a new painted image preserving the features of the source image.
- Barnes, C., Shechtman, E., Finkelstein, A., and Goldman, D. 2009. Patchmatch: A randomized correspondence algorithm for structural image editing. ACM Transactions on Graphics-TOG 28, 3, 24. Google Scholar
Digital Library
- Chang, Y., Saito, S., Uchikawa, K., and Nakajima, M. 2006. Example-based color stylization of images. ACM Transactions on Applied Perception 2, 3, 322--345. Google ScholarDigital Library
- Efros, A. A., and Freeman, W. T. 2001. Image quilting for texture synthesis and transfer. In Proceedings of the 28th annual conference on Computer graphics and interactive techniques, ACM, 341--346. Google ScholarDigital Library
- Felzenszwalb, P. F., and Huttenlocher, D. P. 2004. Efficient graph-based image segmentation. International Journal of Computer Vision 59, 2, 167--181. Google ScholarDigital Library
- Hertzmann, A., Jacobs, C. E., Oliver, N., Curless, B., and Salesin, D. H. 2001. Image analogies. In Proceedings of the 28th annual conference on Computer graphics and interactive techniques, ACM, 327--340. Google ScholarDigital Library
- Kwatra, V., Essa, I., Bobick, A., and Kwatra, N. 2005. Texture optimization for example-based synthesis. In ACM Transactions on Graphics (TOG), vol. 24, ACM, 795--802. Google ScholarDigital Library
- Mital, P. K., Grierson, M., and Smith, T. J. 2013. Corpus-based visual synthesis: an approach for artistic stylization. In Proceedings of the ACM Symposium on Applied Perception, ACM, 51--58. Google ScholarDigital Library
- Reinhard, E., Ashikhmin, M., Gooch, B., and Shirley, P. 2001. Color transfer between images. IEEE Computer graphics and applications 21, 5, 34--41. Google ScholarDigital Library
- Wang, B., Wang, W., Yang, H., and Sun, J. 2004. Efficient example-based painting and synthesis of 2d directional texture. Visualization and Computer Graphics, IEEE Transactions on 10, 3, 266--277. Google ScholarDigital Library
- Zeng, K., Zhao, M., Xiong, C., and Zhu, S.-C. 2009. From image parsing to painterly rendering. ACM Trans. Graph 29, 1, 2. Google ScholarDigital Library
Index Terms
- Region-based painting style transfer
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