Name
Abstract | ||
|---|---|---|
This paper presents a complete, accurate, and efficient solution for the Perspective-n-Line (PnL) problem. Generally, the camera pose can be determined from N ≥ 3 2D-3D line correspondences. The minimal problem (N = 3) and the least-squares problem (N > 3) are generally solved in different ways. This paper shows that a least-squares PnL problem can be transformed into a quadratic equation system that has the same form as the minimal problem. This leads to a unified solution for the minimal and least-squares PnL problems. We adopt the Gram-Schmidt process and a novel hidden variable polynomial solver to increase the numerical stability of our algorithm. Experimental results show that our algorithm is more accurate and robust than the state-of-the-art least-squares algorithms [1]-[4] and is significantly faster. Moreover, our algorithm is more stable than previous minimal solutions [3], [5], [6] with comparable runtime. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/LRA.2020.3047797 | IEEE Robotics and Automation Letters |
Keywords | DocType | Volume |
Localization,perspective-n-line | Journal | 6 |
Issue | ISSN | Citations |
2 | 2377-3766 | 1 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lipu Zhou | 1 | 25 | 5.16 |
| Daniel Koppel | 2 | 1 | 0.34 |
| Michael Kaess | 3 | 1807 | 99.52 |