For the low sparse reconstruction efficiency caused by high resolutions and large volumes of UAV (unmanned aerial vehicle) images, this paper proposes an algorithm for decreasing the number of image pairs and improving the efficiency of outlier removal. Firstly, rough POS (positioning and orientation system) is calculated for each image with the use of GNSS/IMU (Global Navigation Satellite System/inertial measurement unit) data and camera installation angles. Secondly, to reduce image combination complexity, topological connection analysis is used for image pairs selection. Considering high outlier ratios of initial matches, the hierarchical motion consistency constraint (HMCC) is designed to achieve the high efficiency of geometrical verification strategies. The proposed solutions are verified by using four datasets captured with different oblique systems. Results demonstrate that without accuracy sacrifices, the proposed solutions can achieve efficient and reliable reconstruction.