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The primary contribution of this paper is an efficient Structure from Motion(SfM) solution for oblique unmanned aerial vehicle (UAV) images. First, analgorithm, considering spatial relationship constrains between imagefootprints, is designed for match pair selection with assistant of UAV flightcontrol data and oblique camera mounting angles. Second, a topologicalconnection network (TCN), represented by an undirected weighted graph, isconstructed from initial match pairs, which encodes overlap area andintersection angle into edge weights. Then, an algorithm, termed MST-Expansion,is proposed to extract the match graph from the TCN where the TCN is firstlysimplified by a maximum spanning tree (MST). By further analysis of localstructure in the MST, expansion operations are performed on the nodes of theMST for match graph enhancement, which is achieved by introducing criticalconnections in two expansion directions. Finally, guided by the match graph, anefficient SfM solution is proposed, and its validation is verified throughcomprehensive analysis and comparison using three UAV datasets captured withdifferent oblique multi-camera systems. Experiment results demonstrate that theefficiency of image matching is improved with a speedup ratio ranging from 19to 35, and competitive orientation accuracy is achieved from both relativebundle adjustment (BA) without GCPs (Ground Control Points) and absolute BAwith GCPs. At the same time, images in the three datasets are successfullyoriented. For orientation of oblique UAV images, the proposed method can be amore efficient solution.

Efficient Structure from Motion for Oblique UAV Images Based on Maximal Spanning Tree Expansions