Single and multiple rotation averaging iterative optimization coupled 3D reconstruction for low-altitude images using SfM algorithm

doi:10.11947/j.AGCS.2019.20180063

Abstract

Abstract: To reduce the cumulative errors caused by initial stereo model construction and related images augmentation in the existing structure from motion based methods, a single & multiple rotation averaging iterative optimization coupled 3D reconstruction method for low-altitude images is proposed. Firstly, an initial undirected graph of correlated images is established based on images relative orientation. Strongly correlated images are found in terms of the optimal incremental decision function, which is constructed based on multiple factors. Secondly, single rotation averaging considering gross erroris used to expand images directed graph in local reference framework, the global uniform optimal solution of rotation and translation matrices can be computed by quaternion supported multiple rotation averaging without involving 3D points. Finally, bundle adjustment is used to refine 3D points, rotation and translation matrices.The experimental results show that the proposed method can achieve more accurate exterior orientation elements and recover more 3D object points, and significantly improve the efficiency of the incremental structure from motion.

Key words: incremental structure from motion, rotation averaging, incremental decision function, quaternion, exterior orientation elements

CLC Number:

P231

HE Haiqing, CHEN Min, CHEN Ting, LI Dajun, CHEN Xiaoyong. Single and multiple rotation averaging iterative optimization coupled 3D reconstruction for low-altitude images using SfM algorithm[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(6): 688-697.

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