Automated Relative Orientation of UAV-Based Imagery in the Presence of Prior Information for the Flight Trajectory

摘要

UAV-based 3D reconstruction has been used in various applications. However, mitigating the impact of outliers in automatically matched points remains to be a challenging task. Assuming the availability of prior information regarding the UAV trajectory, this paper presents two approaches for reliable estimation of Relative Orientation Parameters (ROPs) in the presence of high percentage of matching outliers. The first approach, which assumes that the UAV platform is moving at a constant flying height while maintaining the camera in a nadir-looking orientation, provides a two-point closed-form solution. The second approach starts from prior information regarding the flight trajectory to define a linearized model, which is augmented with a built-in outlier removal procedure, to estimate a refined set of ROPs. Experimental results from real datasets demonstrate the feasibility of the proposed approaches in providing reliable ROPs from UAV-based imagery in the presence of a high percentage of matching outliers (up to 90 percent).