Manga Colorization
Yingge Qu, Tien-Tsin Wong, Pheng-Ann Heng.
ACM Transcations on Graphics (Proc. of SIGGRAPH'06), Vol. 25, No. 3, pp. 1214--1220, July,
2006. [BibTeX]
Methods for two dimensional stroke based painterly rendering. Effects and applications
Levente Kovács.
University of Pannonia, Veszprém, Hungary,
2006. [BibTeX]
Modeling Plant Structures Using Concept Sketches
Fabricio Anastacio, Mario Costa Sousa, Faramarz Samavati, Joaquim A. Jorge.
NPAR '06: Proceedings of the 4th international symposium on Non-photorealistic animation and rendering, pp. 105--113, New York, NY, USA, June, ACM Press,
2006. [BibTeX]
Multi-scale line drawings from 3D meshes
Alex Ni, Kyuman Jeong, Seungyong Lee, Lee Markosian.
SI3D '06: Proceedings of the 2006 symposium on Interactive 3D graphics and games, pp. 133--137, New York, NY, USA, ACM Press,
2006. [BibTeX]
Natural-looking strokes for drawing applications
Kyoko Murakami, Reiji Tsuruno, Etsuo Genda.
The Visual Computer, Vol. 22, No. 6, pp. 415--423,
2006. [BibTeX]
Non-Photorealistic Rendering in Context: An Observational Study
Tobias Isenberg, Petra Neumann, M. Sheelagh T. Carpendale, Mario Costa Sousa, Joaquim A. Jorge.
NPAR '06: Proceedings of the 4th international symposium on Non-photorealistic animation and rendering, pp. 115--126, New York, NY, USA, June, ACM Press,
2006. [BibTeX]
NPAR by Example: Line Drawing Facial Animation from Photographs
Yuan Luo, Marina L. Gavrilova, Mario Costa Sousa.
International Conference on Computer Graphics, Imaging and Visualisation (CGIV'06), pp. 514--521, Los Alamitos, CA, USA, IEEE Computer Society,
2006. [BibTeX]
Organic Labyrinths and Mazes
Hans Pedersen, Karan Singh.
NPAR '06: Proceedings of the 4th international symposium on Non-photorealistic animation and rendering, pp. 79--86, New York, NY, USA, June, ACM Press,
2006. [BibTeX]
Perceptually-motivated Non-Photorealistic Graphics
Author(s): Holger Winnemöller.
PhD Thesis: Northwestern University, Evanston, Illinois, U.S.A.,
2006.
[BibTeX]
Abstract:
At a high level, computer graphics deals with conveying
information to an observer by visual means. Generating realistic
images for this task requires considerable time and computing
resources. Human vision faces the opposite challenge: to distill
knowledge of the world from a massive influx of visual
information. It is reasonable to assume that synthetic images
based on human perception and tailored for a given task can (1)
decrease image synthesis costs by obviating a physically
realistic lighting simulation, and (2) increase human task
performance by omitting superfluous detail and enhancing visually
important features. This dissertation argues that the connection
between non-realistic depiction and human perception is a
valuable tool to improve the effectiveness of computer-generated
images to support visual communication tasks, and conversely, to
learn more about human perception of such images. Artists have
capitalized on non-realistic imagery to great effect, and have
become masters of conveying complex and even abstract messages by
visual means. The relatively new field of non-photorealistic
computer graphics attempts to harness artists’ implicit expertise
by imitating their visual styles, media, and tools, but only few
works move beyond such simulations to verify the effectiveness of
generated images with perceptual studies, or to investigate which
stylistic elements are effective for a given visual communication
task. This dissertation demonstrates the mutual beneficence of
non-realistic computer graphics and perception with two rendering
frameworks and accompanying psychophysical studies: (1) Inspired
by low-level human perception, a novel image-based abstraction
framework simplifies and enhances images to make them easier to
understand and remember. (2) A non-realistic rendering framework
generates isolated visual shape cues to study human perception of
fast-moving objects. The first framework leverages perception to
increase effectiveness of (non-realistic) images for
visually-driven tasks, while the second framework uses
non-realistic images to learn about task-specific perception,
thus closing the loop. As instances of the bi-directional
connections between perception and non-realistic imagery, the
frameworks illustrate numerous benefits including effectiveness
(e.g. better recognition of abstractions versus photographs),
high performance (e.g. real-time image abstraction), and
relevance (e.g. shape perception in non-impoverished conditions).
Procedural Image Processing for Visualization
Xiaoru Yuan, Baoquan Chen.
Lecture Notes in Computer Science (2nd International Symposium on Visual Computing (ISVC). Lake Tahoe, Nevada. Nov 6-8), Vol. 4291, pp. 50--59, Springer Berlin / Heidelberg,
2006. [BibTeX]