Displacement measurement in large-scale structures (such as excavation walls) is one of the most important applications of close-range photogrammetry, in which achieving high precision requires extracting and accurately matching local features from convergent images. The purpose of this study is to introduce a new multi-image pointing (MIP) algorithm is introduced based on the characteristics of the geometric model generated from the initial matching. This self-adaptive algorithm is used to correct and improve the accuracy of the extracted positions from local features in the convergent images.,In this paper, the new MIP algorithm based on the geometric characteristics of the model generated from the initial matching was introduced, which in a self-adaptive way corrected the extracted image coordinates. The unique characteristics of this proposed algorithm were that the position correction was accomplished with the help of continuous interaction between the 3D model coordinates and the image coordinates and that it had the least dependency on the geometric and radiometric nature of the images. After the initial feature extraction and implementation of the MIP algorithm, the image coordinates were ready for use in the displacement measurement process. The combined photogrammetry displacement adjustment (CPDA) algorithm was used for displacement measurement between two epochs. Micro-geodesy, target-based photogrammetry and the proposed MIP methods were used in a displacement measurement project for an excavation wall in the Velenjak area in Tehran, Iran, to evaluate the proposed algorithm performance. According to the results, the measurement accuracy of the point geo-coordinates of 8 mm and the displacement accuracy of 13 mm could be achieved using the MIP algorithm. In addition to the micro-geodesy method, the accuracy of the results was matched by the cracks created behind the project’s wall. Given the maximum allowable displacement limit of 4 cm in this project, the use of the MIP algorithm produced the required accuracy to determine the critical displacement in the project.,Evaluation of the results demonstrated that the accuracy of 8 mm in determining the position of the points on the feature and the accuracy of 13 mm in the displacement measurement of the excavation walls could be achieved using precise positioning of local features on images using the MIP algorithm.The proposed algorithm can be used in all applications that need to achieve high accuracy in determining the 3D coordinates of local features in close-range photogrammetry.,Some advantages of the proposed MIP photogrammetry algorithm, including the ease of obtaining observations and using local features on the structure in the images rather than installing the artificial targets, make it possible to effectively replace micro-geodesy and instrumentation methods. In addition, the proposed MIP method is superior to the target-based photogrammetric method because it does not need artificial target installation and protection. Moreover, in each photogrammetric application that needs to determine the exact point coordinates on the feature, the proposed algorithm can be very effective in providing the possibility to achieve the required accuracy according to the desired objectives.

中文翻译：

---

应用于会聚近距离摄影测量图像的精确多图像指向 (MIP)

大型结构（如开挖墙）中的位移测量是近景摄影测量最重要的应用之一，其中实现高精度需要从收敛图像中提取并准确匹配局部特征。本研究的目的是根据初始匹配生成的几何模型的特点，介绍一种新的多图像指向（MIP）算法。该自适应算法用于校正和提高收敛图像中局部特征提取位置的精度。,本文介绍了基于初始匹配生成的模型几何特征的新型MIP算法,它以自适应方式校正提取的图像坐标。该算法的独特之处在于，位置校正是在 3D 模型坐标和图像坐标之间连续交互的帮助下完成的，并且它对图像的几何和辐射性质的依赖性最小。在初始特征提取和 MIP 算法实施后，图像坐标已准备好用于位移测量过程。组合摄影测量位移调整（CPDA）算法用于两个时期之间的位移测量。微大地测量学、基于目标的摄影测量和建议的 MIP 方法被用于伊朗德黑兰 Velenjak 地区挖掘墙的位移测量项目，以评估建议的算法性能。根据结果​​，使用MIP算法可以实现点地理坐标的测量精度为8 mm，位移精度为13 mm。除了微大地测量法，结果的准确性与项目墙后产生的裂缝相匹配。鉴于该项目中允许的最大位移限制为 4 cm，使用 MIP 算法产生了确定项目中临界位移所需的精度。结果评估表明，确定该项目位置的精度为 8 mm。通过使用 MIP 算法在图像上精确定位局部特征，可以实现特征上的点和 13 mm 的开挖墙位移测量精度。所提出的算法可用于在近距离摄影测量中需要在确定局部特征的 3D 坐标方面达到高精度的所有应用中。,所提出的 MIP 摄影测量算法的一些优点，包括易于获得观测和使用局部特征图像中的结构而不是安装人工目标，可以有效地替代微大地测量和仪器方法。此外，所提出的 MIP 方法优于基于目标的摄影测量方法，因为它不需要人工目标安装和保护。此外，在每个需要确定要素上精确点坐标的摄影测量应用程序中，