Over the last few decades, the methods of global image orientation, which is also called global SfM, have attracted a lot of attention from researchers, mainly thanks to its advantage of time efficiency. Based on the input of relative orientation results, most conventional global SfM methods employ a two-step strategy consisting of global rotation estimation and global translation estimation. This paper, on the contrary, introduces a hybrid global approach that intends to solve global rotations and translations synchronously, but hierarchically. To improve the robustness and time efficiency, we first propose a novel efficient method that is much faster than the previous approaches for extracting an optimal minimum cover of a connected image triplet set (OMCTS). The OMCTS makes all the available images contained in a minimum number of connected image triplets, as well as all of those selected triplets, satisfy the constraint that the three corresponding relative orientations are as compatible as possible to each other. In order to solve non-collinear triplets in the OMCTS, some fundamental characterizations of essential matrices in the multiple-image setting are used, and image pose parameters are then estimated via averaging the constrained essential matrices. For the collinear triplets, the above approach is invalid and the image pose parameters are then alternatively determined from the relative orientations using the depth of tie points from each individual local spatial intersection. Finally, all image orientations are moved to a common coordinate system by traversing the solved connected triplets using similarity transformations. Compared to the state-of-the-art global SfM methods, the performance and capability of the proposed hybrid approach are thoroughly demonstrated on various public datasets (mainly including ordered and unordered internet images, oblique aerial images, hard and complex datasets, etc.).

在过去的几十年中，主要由于其时间效率的优势，全局图像定向方法（也称为全局SfM）已引起了研究人员的广泛关注。基于相对取向结果的输入，大多数常规的全局SfM方法采用由全局旋转估计和全局平移估计组成的两步​​策略。相反，本文介绍了一种混合全局方法，该方法旨在同步但分层地解决全局旋转和平移。为了提高鲁棒性和时间效率，我们首先提出一种新颖的高效方法，该方法比提取连接的图像三元组（OMCTS）的最佳最小覆盖率的现有方法快得多。OMCTS使包含在最小数量的已连接图像三元组中的所有可用图像，以及所有那些选定的三元组，都满足三个对应的相对方向彼此尽可能兼容的约束。为了解决OMCTS中的非共线三重态，使用了多图像设置中基本矩阵的一些基本特征，然后通过平均约束基本矩阵来估计图像姿态参数。对于共线三元组，上述方法无效，然后使用每个局部空间相交处的结点深度根据相对方向来确定图像姿态参数。最后，通过使用相似变换遍历已求解的已连接三元组，将所有图像方向移动到一个公共坐标系。与最新的全球SfM方法相比，该混合方法的性能和功能已在各种公共数据集上得到了充分证明（主要包括有序和无序互联网图像，倾斜航空图像，硬和复杂数据集等）。 ）。