Non-Photorealistic Computer Graphics Library

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Found 6 item(s) authored by "Suguru Saito" .

Article Curvature-based stroke rendering
Suguru Saito, Akane Kani, Youngha Chang, Masayuki Nakajima.
The Visual Computer, Vol. 24, No. 1, pp. 1--11, 2008. [BibTeX]

Proceedings 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]

Article Example-Based Color Stylization of Images
Youngha Chang, Suguru Saito, Keiji Uchikawa, Masayuki Nakajima.
ACM Transactions on Applied Perception (TAP), Vol. 2, No. 3, pp. 322--345, July, 2005. [BibTeX]

Proceedings Example-based color transformation for image and video
Youngha Chang, Suguru Saito, Masayuki Nakajima.
3rd International Conference on Computer Graphics and Interactive Techniques in Australasia and South East Asia (GRAPHITE'05), pp. 347--353, Dunedin, New Zealand, 2005. [BibTeX]

Proceedings Generation of Varying Line Thickness
Suguru Saito, Akane Kani, Youngha Chang, Masayuki Nakajima.
Computer Graphics International, pp. 294, Tokyo, Japan, July 09 - 11, 2003. [BibTeX]

Proceedings Paintbrush rendering of lines using HMMs

Author(s): Yuta Okabe, Suguru Saito, Masayuki Nakajima.
Proceedings: 3rd International Conference on Computer Graphics and Interactive Techniques in Australasia and South East Asia (GRAPHITE'05), pp. 91--98, Dunedin, New Zealand, 2005.
[BibTeX] [DOI] Find this paper on Google

Abstract:
We propose a new method that emulates the expressive appearance of paintbrush strokes on paper. In our system, brush footprint characteristics are modeled using Hidden Markov Models (HMMs). Once the model is trained by a data set of given strokes, it estimates the most likely sequence of footprints for a given input line. The main difference between our method and other ones that use direct texture mapping lies in the estimation of the dynamic behavior of the footprints with respect to input lines. Since our method models simultaneously the physical characteristics of the brush and the drawing styles, it transforms input lines to aesthetic strokes which are really close to true ones, made with a real brush on a paper.

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