The Pose Estimation of the Aircraft on the Airport Surface Based on the Contour Features

The pose estimation of the aircraft in the taxiing or parking state on the airport surface has been proved helpful for the level of control and command, operation efficiency, capacity of handling special situations of the airports. However, current methods cannot provide satisfied estimate results of the pose of aircrafts because they regard the aircraft as a point. To solve the pose estimation problem of the aircrafts, especially for the small-sized ones, this article proposes an aircraft pose estimation method based on the contour features. First, the contour features of the aircraft are utilized to design a 2-D pose skeleton to show the pose information of the aircraft on the ground. Second, the flux is adopted to represent the two-dimensional aircraft pose skeleton. Finally, a two-branch convolutional neural network is designed to estimate aircraft pose including the aircraft skeleton detection and the aircraft orientation estimation. To overcome the lack of a benchmark dataset, an aircraft dataset was built, and the evaluation of the proposed method's performance on this dataset was also carried out. The experimental results show that our proposed method has satisfied performance compared with other state-of-art approaches on the airport surface aircraft dataset.