Robust merging of subblock reconstructions for parallel structure from motion in photogrammetry
In this paper,we proposed an improved parallel structure from motion pipeline in photogrammetry by robustifying the merging of subblock reconstructions in a better fashion.Specifically,the whole block represented by a view graph is divided into a number of overlapped subblocks via graph partition and expansion,and an improved incremental SfM is employed to gen-erate the SfM reconstruction of each subblock.To merge these subblock SfM reconstructions in a more robust manner,a sub-block graph indicating the overlapping relationship of subblock reconstructions is first built.By considering the geometry con-sistencies of subblock triplets,gross errors are detected.Then,we leverage the algebraic properties of subblock triplets,which aims to make them more geometrically consistent,to refine the relative transformations between subblock reconstructions.Fi-nally,more accurate relative transformations between subblock reconstructions can be obtained to boost the subsequential mer-ging.Experimental results using UAV images show that the proposed method can guarantee robustness in the subblock recon-struction merging stage.The precision of our SfM results is better than several state-of-the-art parallel SfM methods and the popular COLMAP.Furthermore,it has significant potential for use in photogrammetry and 3D Real Scene reconstruction.
photogrammetry3D real sceneUAV imagesparallel structure from motion