Deep Learning-Based Detection and Robust Tracking of an Unmanned Surface Ship Using a Monocular Camera

In this letter, we propose a method for detecting an unmanned ship using image segmentation techniques based on camera images acquired in a marine environment and extracting its relative range and bearing through image processing techniques and geometric information. In addition, a robust Gaussian approximate filter (RGAF) algorithm is proposed that can minimize image processing errors due to the distance between the detecting ship and the target ship and the error due to wave-induced ship movement. Experimental results demonstrate that the proposed image segmentation algorithm is able to accurately detect a moving ship and that the proposed RGAF algorithm is able to estimate the detected ship's position more accurately than the conventional extended Kalman filter (EKF).