Research on the Algorithm of Target Location in Aerial Images under a Large Inclination Angle

Abstract

Target positioning of a large inclination angle in aerial images is challenging for camera distortion, which makes it difficult to obtain a positioning model. Oblique images produce a larger positioning error if a traditional positioning algorithm is directly used to locate the target. To address this problem, this study uses a BP neural network to automatically calculate the high-accuracy positioning of the target. The location algorithm not only does not require camera calibration in advance but also eliminates the impact of camera distortion on target positioning. Through positioning experiments on the collected aerial dataset, the results demonstrate that the average positioning error of the target is about 1m, which has a high-precision positioning result and algorithm robustness.