Name
Abstract | ||
|---|---|---|
We present a novel multiple-linked iterative closest point method to estimate correspondences and the rigid/non-rigid transformations between point-sets or shapes. The estimation task is carried out by maximizing a symmetric similarity function, which is the product of the square roots of correspondences and a kernel correlation. The local mean square error analysis and robustness analysis are provided to show our method's superior performance to the kernel correlation method. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/s10851-010-0230-6 | Journal of Mathematical Imaging and Vision |
Keywords | Field | DocType |
Hellinger distance,Kernel correlation,Monge Kantorovich mass transport problem,Point set registration | Kernel (linear algebra),Point set registration,Mathematical optimization,Radial basis function kernel,Kernel embedding of distributions,Kernel principal component analysis,Variable kernel density estimation,Mathematics,Iterative closest point,Kernel (statistics) | Journal |
Volume | Issue | ISSN |
39 | 2 | 0924-9907 |
Citations | PageRank | References |
0 | 0.34 | 21 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peng-Wen Chen | 1 | 90 | 11.56 |