IEEE Trans Pattern Anal Mach Intell. 2018 Apr;40(4):791-803. doi: 10.1109/TPAMI.2017.2699648. Epub 2017 Apr 28.
We propose a new method to add an uncalibrated node into a network of calibrated cameras using only pairwise point correspondences. While previous methods perform this task using triple correspondences, these are often difficult to establish when there is limited overlap between different views. In such challenging cases we must rely on pairwise correspondences and our solution becomes more advantageous. Our method includes an 11-point minimal solution for the intrinsic and extrinsic calibration of a camera from pairwise correspondences with other two calibrated cameras, and a new inlier selection framework that extends the traditional RANSAC family of algorithms to sampling across multiple datasets. Our method is validated on different application scenarios where a lack of triple correspondences might occur: addition of a new node to a camera network; calibration and motion estimation of a moving camera inside a camera network; and addition of views with limited overlap to a Structure-from-Motion model.
我们提出了一种新方法，仅使用两两点对应关系将未经校准的节点添加到校准相机网络中。虽然以前的方法使用三对点对应关系来执行此任务，但在不同视图之间重叠有限时，这些通常很难建立。在这种具有挑战性的情况下，我们必须依赖两两对应关系，我们的解决方案变得更具优势。我们的方法包括一种 11 点最小解法，用于从与其他两个校准相机的两两对应关系中对相机进行内在和外在校准，以及一种新的内点选择框架，该框架将传统的 RANSAC 算法家族扩展到跨多个数据集进行采样。我们的方法在可能缺少三对点对应关系的不同应用场景中进行了验证：将新节点添加到相机网络中；在相机网络内移动相机的校准和运动估计；以及将具有有限重叠的视图添加到运动结构模型中。
