ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 295-302, 2018
https://doi.org/10.5194/isprs-annals-IV-2-295-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
 
28 May 2018
ROBUST IMAGE ORIENTATION BASED ON RELATIVE ROTATIONS AND TIE POINTS
X. Wang, F. Rottensteiner, and C. Heipke Institute of Photogrammetry and GeoInformation, Leibniz Universität Hannover, Nienburger Str. 1, D-30167 Hannover, Germany
Keywords: image orientation, single rotation averaging, structure from motion (SfM), translation estimation Abstract. In this paper we present a novel approach for image orientation by combining relative rotations and tie points. First, we choose an initial image pair with enough correspondences and large triangulation angle, and we then iteratively add clusters of new images. The rotation of these newly added images is estimated from relative rotations by single rotation averaging. In the next step, a linear equation system is set up for each new image to solve the translation parameters with triangulated tie points which can be viewed in that new image, followed by a resection for refinement. Finally, we optimize the cluster of reconstructed images by local bundle adjustment. We show results of our approach on different benchmark datasets. Furthermore, we orient several larger datasets incl. unordered image datasets to demonstrate the robustness and performance of our approach.
Conference paper (PDF, 2276 KB)

Citation: Wang, X., Rottensteiner, F., and Heipke, C.: ROBUST IMAGE ORIENTATION BASED ON RELATIVE ROTATIONS AND TIE POINTS, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 295-302, https://doi.org/10.5194/isprs-annals-IV-2-295-2018, 2018.

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