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True 3D-information from digital aerial images — Edge detection and adjustment from an oblique viewing multi-camera system

机译:来自数字航空影像的真实3D信息—斜视多镜头系统的边缘检测和调整

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Automated processes for building reconstruction including roof- and façade structures with accuracies better than 0.5 m have not been developed yet. This paper introduces a conceptual approach to derive 3D building edges automatically from oblique aerial imagery. A sub-pixel accurate version of the Canny algorithm is used for detection and segmentation of line segments found on seven oblique true orthomosaics (TOM) mapping a scene from different cardinal directions. With respect to the properties of oblique photogrammetric products and the characteristics of their derivation, all detected line segments are weighted based on their individual camera-target path. An adjustment approach is implemented, which adjusts redundant line segments that are found in several oblique TOM. A validation of the adjustment is done by using tacheometrically measured reference points. On average the approach yields in accuracies of 30 to 35 cm in X, Y and Z.
机译:尚未开发出精确度超过0.5 m的包括屋顶和立面结构在内的建筑物重建自动化程序。本文介绍了一种从倾斜的航空影像中自动得出3D建筑边缘的概念方法。 Canny算法的亚像素精确版本用于检测和分割在七个从不同主方向映射场景的倾斜真实正射影像(TOM)上找到的线段。关于倾斜摄影测量产品的属性及其派生特性,所有检测到的线段均基于其各自的相机目标路径进行加权。实现了一种调整方法,该方法可以调整在多个倾斜TOM中发现的冗余线段。通过使用测速仪测得的参考点来完成调整的验证。平均而言,该方法在X,Y和Z上的精度为30到35 cm。

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