Name
Abstract | ||
|---|---|---|
Signed 3D distance fields are used a in a variety of domains. From shape modelling to surface registration. They are typically computed based on sampled point sets. If the input point set contains holes, the behaviour of the zero-level surface of the distance field is not well defined. In this paper, a novel regularisation approach is described. It is based on an energy formulation, where both local smoothness and data fidelity are included. The minimisation of the global energy is shown to be the solution of a large set of linear equations. The solution to the linear system is found by sparse Cholesky factorisation. It is demonstrated that the zero-level surface will act as a membrane after the proposed regularisation. This effectively closes holes in a predictable way. Finally, the performance of the method is tested with a set of synthetic point clouds of increasing complexity. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-02230-2_52 | SCIA |
Keywords | Field | DocType |
energy formulation,large set,global energy,linear equation,zero-level surface,linear system,distance fields,point set,distance field,synthetic point cloud,input point set,point cloud,linear equations | Linear system,Computer science,Signed distance function,Distance transform,Minimisation (psychology),Artificial intelligence,Smoothness,Cholesky decomposition,Linear equation,Mathematical optimization,Pattern recognition,Algorithm,Point cloud | Conference |
Volume | ISSN | Citations |
5575 | 0302-9743 | 2 |
PageRank | References | Authors |
0.40 | 11 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rasmus R. Paulsen | 1 | 88 | 20.01 |
| Jakob Andreas Bærentzen | 2 | 58 | 7.67 |
| Rasmus Larsen | 3 | 988 | 89.80 |