GPS-assisted feature matching in aerial images with highly repetitive patterns

Matching aerial images might be challenging when they contain a large number of repetitive patterns. In this paper, we propose a feature-matching method that exploits the use of Affine Oriented FAST and Rotated BRIEF (AORB) as keypoint detector and feature descriptor and not accurate GPS (Global Position System) data to achieve a reliable feature matching of nadir UAV images that contain a large number of repetitive patterns. The proposed method assumes that the set of correct matches between two images only differ in a 2D translation. Experimental results show that the proposed method is able to correctly match pairs of very challenging images containing a large number of repetitive patterns.Matching aerial images might be challenging when they contain a large number of repetitive patterns. In this paper, we propose a feature-matching method that exploits the use of Affine Oriented FAST and Rotated BRIEF (AORB) as keypoint detector and feature descriptor and not accurate GPS (Global Position System) data to achieve a reliable feature matching of nadir UAV images that contain a large number of repetitive patterns. The proposed method assumes that the set of correct matches between two images only differ in a 2D translation. Experimental results show that the proposed method is able to correctly match pairs of very challenging images containing a large number of repetitive patterns.C