Camera Pose Estimation from Lines using Plücker Coordinates
This work addresses camera localization in computer vision, particularly for scenarios with many lines, but it is incremental as it builds on existing line-based methods with improvements in speed and simplicity.
The authors tackled the problem of camera pose estimation from 3D-to-2D line correspondences by proposing a novel algebraic algorithm using Plücker coordinates, which is an order of magnitude faster than state-of-the-art methods while maintaining comparable accuracy and robustness.
Correspondences between 3D lines and their 2D images captured by a camera are often used to determine position and orientation of the camera in space. In this work, we propose a novel algebraic algorithm to estimate the camera pose. We parameterize 3D lines using Plücker coordinates that allow linear projection of the lines into the image. A line projection matrix is estimated using Linear Least Squares and the camera pose is then extracted from the matrix. An algebraic approach to handle mismatched line correspondences is also included. The proposed algorithm is an order of magnitude faster yet comparably accurate and robust to the state-of-the-art, it does not require initialization, and it yields only one solution. The described method requires at least 9 lines and is particularly suitable for scenarios with 25 and more lines, as also shown in the results.