Directional Texture Transfer With Edge Enhancement
Hochang Lee, Sanghyun Seo, Kyunghyun Yoon.
Computers & Graphics, Vol. 35, No. 1, pp. 81--91,
2011. [BibTeX]
GPU-based SoftAssign for Maximizing Image Utilization in Photomosaics
Marcos Slomp, Michihiro Mikamo, Bisser Raytchev, Toru Tamaki, Kazufumi Kaneda.
International Journal of Networking and Computing, Vol. 1, No. 2, pp. 211--229, July,
2011. [BibTeX]
Image and Video Abstraction by Coherence-Enhancing Filtering
Jan Eric Kyprianidis, Henry Kang.
Computer Graphics Forum, Vol. 30, No. 2, pp. 593--602,
2011. [BibTeX]
Real-Time Shape Illustration Using Laplacian Lines
Author(s): Long Zhang, Ying He, Jiazhi Xia, Xuexiang Xie, Wei Chen.
Article: IEEE Transactions on Visualization and Computer Graphics, Vol. 17, No. 7, pp. 993--1006, july,
2011.
[BibTeX] [DOI] 
Abstract:
This paper presents a novel object-space line drawing algorithm that can depict shapes with view-dependent feature lines in real time. Strongly inspired by the Laplacian-of-Gaussian (LoG) edge detector in image processing, we define Laplacian lines as the zero-crossing points of the Laplacian of the surface illumination. Compared to other view-dependent feature lines, Laplacian lines are computationally efficient because most expensive computations can be preprocessed. We further extend Laplacian lines to volumetric data and develop the algorithm to compute volumetric Laplacian lines without isosurface extraction. We apply the proposed Laplacian lines to a wide range of real-world models and demonstrate that Laplacian lines are more efficient than the existing computer generated feature lines, and can be used in interactive graphics applications.