Real-Time Exemplar-Based Face Sketch Synthesis
Conference paper
Abstract
This paper proposes a simple yet effective face sketch synthesis method. Similar to existing exemplar-based methods, a training dataset containing photo-sketch pairs is required, and a K-NN photo patch search is performed between a test photo and every training exemplar for sketch patch selection. Instead of using the Markov Random Field to optimize global sketch patch selection, this paper formulates face sketch synthesis as an image denoising problem which can be solved efficiently using the proposed method. Real-time performance can be obtained on a state-of-the-art GPU. Meanwhile quantitative evaluations on face sketch recognition and user study demonstrate the effectiveness of the proposed method. In addition, the proposed method can be directly extended to the temporal domain for consistent video sketch synthesis, which is of great importance in digital entertainment.
Keywords
Face Hallucination Texture Synthesis Download
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References
- 1.Adobe: Adobe photoshop cs6Google Scholar
- 2.Aleix, M., Robert, B.: The ar face database. Tech. Rep. CVC Technical Report 24, Purdue University (1998)Google Scholar
- 3.Altman, N.S.: An introduction to kernel and nearest-neighbor nonparametric regression. The American Statistician (1992)Google Scholar
- 4.Barnes, C., Shechtman, E., Finkelstein, A., Goldman, D.: Patchmatch: a randomized correspondence algorithm for structural image editing. In: SIGGRAPH (2009)Google Scholar
- 5.Berger, I., Shamir, A., Mahler, M., Carter, E., Hodgins, J.: Style and abstraction in portrait sketching. In: SIGGRAPH (2013)Google Scholar
- 6.Buades, A., Coll, B., Morel, J.M.: A non-local algorithm for image denoising. In: CVPR (2005)Google Scholar
- 7.Chen, H., Xu, Y.Q., Shum, H.Y., Zhu, S.C., Zheng, N.N.: Example-based facial sketch generation with non-parametric sampling. In: ICCV (2001)Google Scholar
- 8.Dabov, K., Foi, A., Katkovnik, V., Egiazarian, K.: Image denoising by sparse 3-d transform-domain collaborative filtering. TIP (2007)Google Scholar
- 9.Delac, K., Grgic, M., Grgic, S.: Independent comparative study of pca, ica, and lda on the feret data set. IJIST (2005)Google Scholar
- 10.Freeman, W.T., Tenenbaum, J.B., Pasztor, E.: An example-based approach to style translation for line drawings. MERL Technical Report (1999)Google Scholar
- 11.Gastal, E.S., Oliveira, M.M.: Domain transform for edge-aware image and video processing. In: SIGGRAPH (2011)Google Scholar
- 12.Hertzmann, A., Jacobs, C.E., Oliver, N., Curless, B., Salesin, D.H.: Image analogies. In: SIGGRAPH (2001)Google Scholar
- 13.Liu, Q., Tang, X., Jin, H., Lu, H., Ma, S.: A nonlinear approach for face sketch synthesis and recognition. In: CVPR (2005)Google Scholar
- 14.Lu, C., Xu, L., Jia, J.: Combining sketch and tone for pencil drawing production. In: NPAR (2012)Google Scholar
- 15.Paige, C.C., Saunders, M.A.: Lsqr: An algorithm for sparse linear equations and sparse least squares. ACM Transactions on Mathematical Software (1982)Google Scholar
- 16.Tang, X., Wang, X.: Face sketch synthesis and recognition. In: CVPR (2003)Google Scholar
- 17.Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: CVPR (2001)Google Scholar
- 18.Wang, S., Zhang, L.: Y., L., Pan, Q.: Semi-coupled dictionary learning with applications in image super-resolution and photo-sketch synthesis. In: CVPR (2012)Google Scholar
- 19.Wang, X., Tang, X.: Face photo-sketch synthesis and recognition. PAMI (2009)Google Scholar
- 20.Wright, J., Yang, A.Y., Ganesh, A., Sastry, S.S., Ma, Y.: Robust face recognition via sparse representation. PAMI (2009)Google Scholar
- 21.Xu, Z., Chen, H., Zhu, S.C., Luo, J.: A hierarchical compositional model for face representation and sketching. PAMI (2008)Google Scholar
- 22.Zhang, W., Wang, X., Tang, X.: Lighting and pose robust face sketch synthesis. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part VI. LNCS, vol. 6316, pp. 420–433. Springer, Heidelberg (2010)CrossRefGoogle Scholar
- 23.Zhang, W., Wang, X., Tang, X.: Coupled information-theoretic encoding for face photo-sketch recognition. In: CVPR (2011)Google Scholar
- 24.Zhou, H., Kuang, Z., Wong, K.: Markov weight fields for face sketch synthesis. In: CVPR (2012)Google Scholar
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