Name
Abstract | ||
|---|---|---|
This paper proposes a non-rigid registration formulation capturing both global and local deformations in a single framework. This formulation is based on a quadratic estimation of the registration distance together with a quadratic regularization term. Hence, the optimal transformation parameters are easily obtained by solving a liner system of equations, which guarantee a fast convergence. Experimental results with challenging 2D and 3D shapes are presented to show the validity of the proposed framework. Furthermore, comparisons with the most relevant approaches are provided. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-33786-4_20 | ECCV (7) |
Keywords | Field | DocType |
non-rigid shape registration,registration distance,single framework,quadratic estimation,proposed framework,non-rigid registration formulation,squares framework,local deformation,fast convergence,liner system,quadratic regularization term | Convergence (routing),Computer vision,Applied mathematics,Mathematical optimization,Thin plate spline,System of linear equations,Computer science,3d shapes,Quadratic equation,Regularization (mathematics),Artificial intelligence,Linear least squares | Conference |
Volume | ISSN | Citations |
7578 | 0302-9743 | 7 |
PageRank | References | Authors |
0.47 | 18 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohammad Rouhani | 1 | 51 | 5.30 |
| Angel Domingo Sappa | 2 | 565 | 33.54 |