Name
Abstract | ||
|---|---|---|
In this paper we show that a Geometric Algebra-based least-mean-squares adaptive filter (GA-LMS) can be used to recover the 6-degree-of-freedom alignment of two point clouds related by a set of point correspondences. We present a series of techniques that endow the GA-LMS with outlier (false correspondence) resilience to outperform standard least squares (LS) methods that are based on Singular Value Decomposition (SVD). We furthermore show how to derive and compute the step size of the GA-LMS. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/WACV.2016.7477642 | 2016 IEEE Winter Conference on Applications of Computer Vision (WACV) |
Keywords | Field | DocType |
6DOF point cloud alignment,geometric algebra,adaptive filtering,least-mean-squares,GA-LMS,6-degree-of-freedom alignment,singular value decomposition,SVD | Least squares,Singular value decomposition,Pattern recognition,Computer science,Matrix (mathematics),Outlier,Artificial intelligence,Adaptive filter,Geometric algebra,Point cloud,Recursive least squares filter | Conference |
Citations | PageRank | References |
1 | 0.38 | 19 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anas Al-Nuaimi | 1 | 79 | 6.86 |
| Eckehard G. Steinbach | 2 | 2221 | 299.71 |
| Wilder Bezerra Lopes | 3 | 22 | 2.63 |
| Cássio Guimarães Lopes | 4 | 394 | 32.32 |