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Adaptive Image Translation for Painterly Rendering
Author(s): Kenji Hara, Kohei Inoue, Kiichi Urahama.
Proceedings: IAPR Conference on Machine Vision Applications (MVA2005), pp. 566--569,
2005.
[BibTeX] 
Abstract:
In the paper, we present a new method of converting a photo image to a synthesized painting image following the painting style of an example painting image. The proposed method uses a hierarchical and adaptive patch-based approach to both the synthesis of painting styles and preservation of scene details. This approach can be summarized as follows. The input photo image is represented as a set of patches divided adaptively using a distance transform technique. Then the mapping between the input photo and example painting images is efficiently inferred using Bayesian belief propagation recursively.