In this paper, we propose the first minimal solutions for estimating the semi-generalized homography given a perspective and a generalized camera. The proposed solvers use five 2D-2D image point correspondences induced by a scene plane. One of them assumes the perspective camera to be fully calibrated, while the other solver estimates the unknown focal length together with the absolute pose parameters. This setup is particularly important in structure-from-motion and image-based localization pipelines, where a new camera is localized in each step with respect to a set of known cameras and 2D-3D correspondences might not be available. As a consequence of a clever parametrization and the elimination ideal method, our approach only needs to solve a univariate polynomial of degree five or three. The proposed solvers are stable and efficient as demonstrated by a number of synthetic and real-world experiments.
翻译:在本文中,我们提出了以视角和通用相机来估计半通用同系物的第一个最起码的解决方案。 推荐的解答器使用由场景平面引发的5个 2D-2D 图像点对应物。 其中1个假设角度相机完全校准, 而另一个解答器则估计未知焦线长度以及绝对表面参数。 这一设置在结构- 动和图像- 本地化管道中特别重要, 在每个步骤中, 可能无法找到一套已知的相机和2D-3D 通信。 由于智能的对称法和消灭理想方法, 我们的方法只需要解决一个5或3级的单面多面体多面体。 推荐的解答器是稳定和高效的, 正如一系列合成和真实世界实验所证明的那样。