Dependency-Free Parallel Progressive Meshes
Article first published online: 9 JUL 2012
© 2012 The Authors Computer Graphics Forum © 2012 The Eurographics Association and Blackwell Publishing Ltd.
Computer Graphics Forum
Volume 31, Issue 8, pages 2288–2302, December 2012
How to Cite
Derzapf, E. and Guthe, M. (2012), Dependency-Free Parallel Progressive Meshes. Computer Graphics Forum, 31: 2288–2302. doi: 10.1111/j.1467-8659.2012.03154.x
- Issue published online: 26 OCT 2012
- Article first published online: 9 JUL 2012
- level of detail algorithms;
- real-time rendering;
- data compression
- I.3.5 [Computer Graphics]: Computational Geometry and Object Modelling—Curve, surface, solid, and object representations;
- I.3.3 [Computer Graphics]: Picture/Image Generation Display algorithms;
- I.3.1 [Computer Graphics]: Hardware architecture Parallel processing
The constantly increasing complexity of polygonal models in interactive applications poses two major problems. First, the number of primitives that can be rendered at real-time frame rates is currently limited to a few million. Secondly, less than 45 million triangles—with vertices and normal—can be stored per gigabyte. Although the rendering time can be reduced using level-of-detail (LOD) algorithms, representing a model at different complexity levels, these often even increase memory consumption. Out-of-core algorithms solve this problem by transferring the data currently required for rendering from external devices. Compression techniques are commonly used because of the limited bandwidth. The main problem of compression and decompression algorithms is the only coarse-grained random access. A similar problem occurs in view-dependent LOD techniques. Because of the interdependency of split operations, the adaption rate is reduced leading to visible popping artefacts during fast movements. In this paper, we propose a novel algorithm for real-time view-dependent rendering of gigabyte-sized models. It is based on a neighbourhood dependency-free progressive mesh data structure. Using a per operation compression method, it is suitable for parallel random-access decompression and out-of-core memory management without storing decompressed data.