Name
Abstract | ||
|---|---|---|
In this paper, we propose a new approach for point cloud registration based on a volumetric representation called the vector field. A surface classification method is first integrated in the vector field represention to implement rough registration estimation in a pair-wise manner. A pose refinement process is then applied to the rough-estimate. The global registration process is supported entirely by the vector field representation. It does not require a priori information on relative position of views and reduces the computational complexity for searching correspondences. Experiments demonstrate the efficiency of the method on a wide variety of objects. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/CRV.2011.24 | CRV |
Keywords | Field | DocType |
computational geometry,surface roughness,shape,computational complexity,vector field,nickel,point cloud,image registration,image classification,estimation | Computer vision,Pattern recognition,Vector field,Computer science,Image representation,A priori and a posteriori,Computational geometry,Artificial intelligence,Point cloud,Contextual image classification,Image registration,Computational complexity theory | Conference |
Citations | PageRank | References |
3 | 0.41 | 7 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Van Tung Nguyen | 1 | 6 | 0.81 |
| Denis Laurendeau | 2 | 803 | 169.72 |