Name
Abstract | ||
|---|---|---|
We illustrate a method that performs scan matching by maximizing the intersection area of the scans. The intersection area is a robust parameter that is less prone to measurement errors with respect to alternative techniques. Furthermore, such technique does not require to associate each point of one scan to a point of the other one like in some popular algorithms. The relative pose that maximizes the overlap is estimated iteratively. Since the scans are represented by star-shaped polygons due to visibility properties, their intersection can be computed using an efficient linear-time traversal of the vertices. Then, the relative pose is updated under the hypothesis that the combinatorics of intersection is left unchanged and the procedure is repeated until the scans are aligned with sufficient precision. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ECMR.2013.6698823 | ECMR |
Keywords | Field | DocType |
computational geometry,pattern matching,pose estimation | Computer vision,Polygon,Visibility,Tree traversal,Vertex (geometry),Computer science,Computational geometry,Pose,Artificial intelligence,Pattern matching,Observational error | Conference |
Citations | PageRank | References |
0 | 0.34 | 16 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dario Lodi Rizzini | 1 | 83 | 12.58 |
| Stefano Caselli | 2 | 314 | 36.32 |