Dynamic Presentations for Illustration Purposes
Roland Jesse.
Otto-von-Guericke-Universität Magdeburg, March,
2004. [BibTeX]
Dynamics by Hybrid Combination of Photorealistic and Non-Photorealistic Rendering Styles
Roland Jesse, Tobias Isenberg, Bernd Nettelbeck, Thomas Strothotte.
Department of Computer Science, University of Magdeburg, No. 5/2004, Germany,
2004. [BibTeX]
Efficient Coding of Stroke-rendered Paintings
Levente Kovács, Tamás Szirányi.
International Conference on Pattern Recognition (ICPR'04), Vol. 2, pp. 835--838, 23-26 August,
2004. [BibTeX]
Efficient Example-Based Painting and Synthesis of 2D Directional Texture
Bin Wang, Wenping Wang, Huaiping Yang, Jiaguang Sun.
IEEE Transactions on Visualization and Computer Graphics, Vol. 10, No. 3, pp. 266--277,
2004. [BibTeX]
Enhanced LIC Pencil Filter
Shigefumi Yamamoto, Xiaoyang Mao, Kenji Tanii, Atsumi Imamiya.
International Conference on Computer Graphics, Imaging and Visualization (CGIV'04), pp. 251--256, July,
2004. [BibTeX]
Enhancing perceived depth in images via artistic matting
Amy A. Gooch, Bruce Gooch.
1st Symposium on Applied perception in graphics and visualization,
2004. [BibTeX]
Example-based color stylization based on categorical perception
Youngha Chang, Keiji Uchikawa, Suguru Saito, Masayuki Nakajima.
1st Symposium on Applied perception in graphics and visualization, pp. 91--98, ACM Press,
2004. [BibTeX]
Example-Based Composite Sketching of Human Portraits
Hong Chen, Ziqiang Liu, Chuck Rose, Ying-Qing Xu, Heung-Yeung Shum, David H. Salesin.
3rd International Symposium on Non-Photorealistic Animation and Rendering (NPAR'04),
2004. [BibTeX]
Example-based Style Synthesis
Iddo Drori, Daniel Cohen-Or, Hezy Yeshurun.
Computer Vision and Pattern Recognition (CVPR '03), Vol. 2, pp. 143--150, 18-20 June,
2004. [BibTeX]
Expressive Painterly Rendering Through Image Processing
Author(s): Jason Douglas Waltman.
Master Thesis: School of Computing, University of Utah, May,
2004.
[BibTeX] 
Abstract:
In real paintings, a human is in control of every aspect of the painting creation process and, as a result, these works of art are seemingly more valued than their photographic equivalents. The human painter is able not only to document a scene but also to add expressive elements—for example, a stylized abstraction combined with exaggerated brushwork—not possible in a photograph of the same scene. Automatic, computer-generated, photograph-to-painterly rendering techniques have been published now for over a decade. In general, these techniques produce images that lack characteristics found in paintings created by human hands. A new painterly rendering technique is presented which employs digital image processing, computer vision, and emulation of details found in works by painting masters in order to produce images with human expressive characteristics and important details found in real paintings.