A Resolution Independent Nonrealistic Imaging System for Artistic Use
Atsushi Kasao, Masayuki Nakajima.
IEEE International Conference on Multimedia Computing and Systems, pp. 358--367,
1998. [BibTeX]
Curvature-based stroke rendering
Suguru Saito, Akane Kani, Youngha Chang, Masayuki Nakajima.
The Visual Computer, Vol. 24, No. 1, pp. 1--11,
2008. [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 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]
Example-based color transformation for image and video
Author(s): Youngha Chang, Suguru Saito, Masayuki Nakajima.
Proceedings: 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] [DOI]
Abstract:
Color is very important in setting the mood of images and video sequences. For this reason, color transformation is one of the most important features in photo-editing or video post-production tools because even slight modifications of colors in an image can strongly increase its visual appeal. However, conventional color editing tools require user's manual operation for detailed color manipulation. Such manual operation becomes burden especially when editing video frame sequences. To avoid this problem, we previously suggested a method [Chang et al. 2004] that performs an examplebased color stylization of images using perceptual color categories. In this paper, we extend this method to make the algorithm more robust and to stylize the colors of video frame sequences. The main extension is the following 5 points: applicable to images taken under a variety of light conditions; speeding up the color naming step; improving the mapping between source and reference colors when there is a disparity in size of the chromatic categories; separate handling of achromatic categories from chromatic categories; and extending the algorithm along the temporal axis to allow video processing. We present a variety of results, arguing that these images and videos convey a different, but coherent mood.
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]
Paintbrush rendering of lines using HMMs
Yuta Okabe, Suguru Saito, Masayuki Nakajima.
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]
Volumetric Modeling of Colored Pencil Drawing
Saeko Takagi, Masayuki Nakajima, Issei Fujishiro.
7th Pacific Conference on Computer Graphics and Applications (PG'99), pp. 250--258, Seoul, Korea, October 05 - 07,
1999. [BibTeX]