Name
Abstract | ||
|---|---|---|
The problem of geometric alignment of two roughly preregistered, partially overlapping, rigid, noisy 3D point sets is considered. A new natural and simple, robustified extension of the popular Iterative Closest Point (ICP) algorithm (Besl and McKay, 1992) is presented, called the Trimmed ICP (TrICP). The new algorithm is based on the consistent use of the least trimmed squares (LTS) approach in all phases of the operation. Convergence is proved and an efficient implementation is discussed. TrICP is fast, applicable to overlaps under 50%, robust to erroneous measurements and shape defects, and has easy-to-set parameters. ICP is a special case of TrICP when the overlap parameter is 100%. Results of testing the new algorithm are shown. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1109/ICPR.2002.1047997 | Pattern Recognition, 2002. Proceedings. 16th International Conference |
Keywords | Field | DocType |
image matching,image motion analysis,image registration,least mean squares methods,Trimmed ICP,Trimmed Iterative Closest Point algorithm,convergence,geometric alignment,image registration,least trimmed squares approach,mean square error,motion analysis,partially overlapping 3D point sets,rigid noisy 3D point sets,shape defects | Convergence (routing),Computer vision,Least trimmed squares,Pattern recognition,Image matching,Computer science,Algorithm,Artificial intelligence,Image registration,Special case,Iterative closest point,Geometric alignment | Conference |
Volume | ISSN | ISBN |
3 | 1051-4651 | 0-7695-1695-X |
Citations | PageRank | References |
113 | 5.17 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chetverikov, D. | 1 | 956 | 99.89 |
| Svirko, D. | 2 | 113 | 5.17 |
| Stepanov, D. | 3 | 113 | 5.17 |
| Pavel Krsek | 4 | 229 | 10.77 |