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| Content Provider | Springer Nature Link |
|---|---|
| Author | Wang, Lujin Gu, Xianfeng Mueller, Klaus Yau, Shing Tung |
| Copyright Year | 2005 |
| Abstract | Texture mapping and texture synthesis are two popular methods for the decoration of surfaces with visual detail. Here, an existing challenge is to preserve, or at least balance, two competing metrics: scale and angle. In this paper we present two methods for this, both based on global conformal parameterization. First, we describe a texture synthesis algorithm for surfaces with arbitrary topology. By using the conformal parameterization, the 3D surface texture synthesis problem can be converted to a 2D image synthesis problem, which is more intuitive, easier, and conceptually simpler. While the conformality of the parameterization naturally preserves the angles of the texture, in this paper we provide a multi-scale technique to also maintain a more uniform area scaling factor. A second novel contribution is to employ the global parameterization to simultaneously preserve orthogonality and size in texture mapping. For this, we show that a conformal factor-driven mass-spring method offers a convenient way to trade off these two qualitative metrics. Our algorithms are simple, efficient and automatic, and they are theoretically sound and universal to general surfaces as well. |
| Starting Page | 801 |
| Ending Page | 810 |
| Page Count | 10 |
| File Format | |
| ISSN | 01782789 |
| Journal | The Visual Computer |
| Volume Number | 21 |
| Issue Number | 8-10 |
| e-ISSN | 14322315 |
| Language | English |
| Publisher | Springer-Verlag |
| Publisher Date | 2005-09-01 |
| Publisher Place | Berlin, Heidelberg |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Texture synthesis Texture mapping Riemann surfaces Global conformal parameterization Computer Science Artificial Intelligence (incl. Robotics) Image Processing Computer Graphics |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Graphics and Computer-Aided Design Computer Vision and Pattern Recognition Software |
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