  This work is concerned with camera pose estimation from correspondences of
3D/2D lines, i. e. with the Perspective-n-Line (PnL) problem. We focus on large
line sets, which can be efficiently solved by methods using linear formulation
of PnL. We propose a novel method "DLT-Combined-Lines" based on the Direct
Linear Transformation (DLT) algorithm, which benefits from a new combination of
two existing DLT methods for pose estimation. The method represents 2D
structure by lines, and 3D structure by both points and lines. The redundant 3D
information reduces the minimum required line correspondences to 5. A
cornerstone of the method is a combined projection matri xestimated by the DLT
algorithm. It contains multiple estimates of camera rotation and translation,
which can be recovered after enforcing constraints of the matrix. Multiplicity
of the estimates is exploited to improve the accuracy of the proposed method.
For large line sets (10 and more), the method is comparable to the
state-of-theart in accuracy of orientation estimation. It achieves
state-of-the-art accuracy in estimation of camera position and it yields the
smallest reprojection error under strong image noise. The method achieves top-3
results on real world data. The proposed method is also highly computationally
effective, estimating the pose of 1000 lines in 12 ms on a desktop computer.
