Poisson Vector Graphics (PVG)
Published in IEEE Transactions on Visualization and Computer Graphics, 2018
Abstract: This paper presents Poisson vector graphics (PVG), an extension of the popular diffusion curves (DC), for generating smooth-shaded images. Armed with two new types of primitives, called Poisson curves and Poisson regions, PVG can easily produce photorealistic effects such as specular highlights, core shadows, translucency and halos. Within the PVG framework, the users specify color as the Dirichlet boundary condition of diffusion curves and control tone by offsetting the Laplacian of colors, where both controls are simply done by mouse click and slider dragging. PVG distinguishes itself from other diffusion based vector graphics for 3 unique features: 1) explicit separation of colors and tones, which follows the basic drawing principle and eases editing; 2) native support of seamless cloning in the sense that PCs and PRs can automatically fit into the target background; and 3) allowed intersecting primitives (except for DC-DC intersection) so that users can create layers. Through extensive experiments and a preliminary user study, we demonstrate that PVG is a simple yet powerful authoring tool that can produce photo-realistic vector graphics from scratch.
Recommended citation: Fei Hou, Qian Sun, Zheng Fang, Yong-Jin Liu, Shi-Min Hu, Hong Qin, Aimin Hao, Ying He. Poisson Vector Graphics (PVG). IEEE Transactions on Visualization and Computer Graphics, Vol. 26, No. 2, pp. 1361-1371, 2020.