Name
Abstract | ||
|---|---|---|
Efficient data synchronization for 3D mesh models is a new major challenge. 3D models are also now being used to an increasing extent and with current network technology, 3D model compression, visualization and protection demand increases. However, there is still no perfect method to achieve this data synchronization while being blind and robust against various attacks. We propose a blind method based on a Hamiltonian path to synchronize vertex clouds, and particularly on 3D meshes. We experimentally show that it is fast and robust against Gaussian noise. This novel approach can generate better results than mesh-based methods because it does not use vertex connectivity. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/MMSP.2013.6659272 | MMSP |
Keywords | Field | DocType |
Gaussian noise,data encapsulation,mesh generation,synchronisation,watermarking,3D mesh models,3D model compression,Gaussian noise,blind method,data synchronization,protection demand,robust Hamiltonian path,vertex cloud,visualization | Polygon mesh,Computer science,Hamiltonian path,Theoretical computer science,Artificial intelligence,Computer vision,Topology,Synchronization,Vertex (geometry),Visualization,Data synchronization,Gaussian noise,Mesh generation | Conference |
ISSN | Citations | PageRank |
2163-3517 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vincent Itier | 1 | 14 | 4.32 |
| William Puech | 2 | 535 | 76.74 |
| Jean-Pierre Pedeboy | 3 | 0 | 2.03 |
| Gilles Gesquière | 4 | 50 | 11.31 |