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.
关键词
摄影测量/实景三维/无人机影像/并行式运动恢复结构
Key words
photogrammetry/3D real scene/UAV images/parallel structure from motion
维普
万方数据