Our method provides a compact and explicit representation of diffusion curve images for texture mapping onto a surface. The sharp features and detailed color variations of textures are well preserved in the rendering results.
We introduce a vector representation called diffusion curve textures for mapping diffusion curve images (DCI) onto arbitrary surfaces. In contrast to the original implicit representation of DCIs [Orzan et al. 2008], where determining a single texture value requires iterative computation of the entire DCI via the Poisson equation, diffusion curve textures provide an explicit representation from which the texture value at any point can be solved directly, while preserving the compactness and resolution independence of diffusion curves. This is achieved through a formulation of the DCI diffusion process in terms of Green’s functions. This formulation furthermore allows the texture value of any rectangular region (e.g. pixel area) to be solved inclosed form, which facilitates anti-aliasing. We develop a GPU algorithm that renders anti-aliased diffusion curve textures in real time, and demonstrate the effectiveness of this method through high quality renderings with detailed control curves and color variations
Keywordsvector images; diffusion curves; texture mapping and rendering DownloadsBibTex@article{Sun:2012:DCT, author = {Sun, Xin and Xie, Guofu and Dong, Yue and Lin, Stephen and Xu, Weiwei and Wang, Wencheng and Tong, Xin and Guo, Baining}, title = {Diffusion curve textures for resolution independent texture mapping}, journal = {ACM Trans. Graph.}, issue_date = {July 2012}, volume = {31}, number = {4}, month = jul, year = {2012}, issn = {0730-0301}, pages = {74:1--74:9}, articleno = {74}, numpages = {9}, url = {http://doi.acm.org/10.1145/2185520.2185570}, doi = {10.1145/2185520.2185570}, acmid = {2185570}, publisher = {ACM}, address = {New York, NY, USA}, keywords = {diffusion curves, texture mapping and rendering, vector images}, } |
AcknowledgementsWe would like to thank the reviewers for their valuable comments. Guofu Xie and Wencheng Wang were partially supported by NSF of China (60833007). |