Edge‐Friend: Fast and Deterministic Catmull‐Clark Subdivision Surfaces
We present edge‐friend , a data structure for quad meshes with access to neighborhood information required for Catmull‐Clark subdivision surface refinement. Edge‐friend enables efficient real‐time subdivision surface rendering. In particular, the resulting algorithm is deterministic, does not requir...
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| Vydané v: | Computer graphics forum Ročník 42; číslo 8 |
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| Hlavní autori: | , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Oxford
Blackwell Publishing Ltd
01.12.2023
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| Predmet: | |
| ISSN: | 0167-7055, 1467-8659 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | We present
edge‐friend
, a data structure for quad meshes with access to neighborhood information required for Catmull‐Clark subdivision surface refinement. Edge‐friend enables efficient real‐time subdivision surface rendering. In particular, the resulting algorithm is deterministic, does not require hardware support for atomic floating‐point arithmetic, and is optimized for efficient rendering on GPUs. Edge‐friend exploits that after one subdivision step, two edges can be uniquely and implicitly assigned to each quad. Additionally, edge‐friend is a compact data structure, adding little overhead. Our algorithm is simple to implement in a single compute shader kernel, and requires minimal synchronization which makes it particularly suited for asynchronous execution. We easily extend our kernel to support relevant Catmull‐Clark subdivision surface features, including semi‐smooth creases, boundaries, animation and attribute interpolation. In case of topology changes, our data structure requires little preprocessing, making it amendable for a variety of applications, including real‐time editing and animations. Our method can process and render billions of triangles per second on modern GPUs. For a sample mesh, our algorithm generates and renders 2.9 million triangles in 0.58ms on an AMD Radeon RX 7900 XTX GPU. |
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| Bibliografia: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 0167-7055 1467-8659 |
| DOI: | 10.1111/cgf.14863 |