Name
Abstract | ||
|---|---|---|
Surface parameterizations and registrations are important in computer graphics and imaging, where 1-1 correspondences between meshes are computed. In practice, surface maps are usually represented and stored as 3D coordinates each vertex is mapped to, which often requires lots of storage memory. This causes inconvenience in data transmission and data storage. To tackle this problem, we propose an effective algorithm for compressing surface homeomorphisms using Fourier approximation of the Beltrami representation. The Beltrami representation is a complex-valued function defined on triangular faces of the surface mesh with supreme norm strictly less than 1. Under suitable normalization, there is a 1-1 correspondence between the set of surface homeomorphisms and the set of Beltrami representations. Hence, every bijective surface map is associated with a unique Beltrami representation. Conversely, given a Beltrami representation, the corresponding bijective surface map can be exactly reconstructed using the Linear Beltrami Solver introduced in this paper. Using the Beltrami representation, the surface homeomorphism can be easily compressed by Fourier approximation, without distorting the bijectivity of the map. The storage memory can be effectively reduced, which is useful for many practical problems in computer graphics and imaging. In this paper, we proposed to apply the algorithm to texture map compression and video compression. With our proposed algorithm, the storage requirement for the texture properties of a textured surface can be significantly reduced. Our algorithm can further be applied to compressing motion vector fields for video compression, which effectively improve the compression ratio. |
Year | Venue | Field |
|---|---|---|
2012 | CoRR | Computer vision,Texture mapping,Bijection,Polygon mesh,Computer science,Surface map,Artificial intelligence,Data compression,Computer graphics,Homeomorphism,Motion vector |
DocType | Volume | Citations |
Journal | abs/1210.8025 | 2 |
PageRank | References | Authors |
0.37 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lok Ming Lui | 1 | 332 | 30.16 |
| Ka Chun Lam | 2 | 78 | 7.33 |
| Tsz Wai Wong | 3 | 80 | 4.82 |
| Xianfeng Gu | 4 | 2997 | 189.71 |