This paper resolves the problem of detecting small drones in surveillance videos using deep learning algorithms. Single Shot Detector (SSD) object detection algorithm and MobileNet-v2 architecture as the backbone were used for our experiments. The pretrained model was re-trained on custom drone synthetic dataset by using transfer learning’s fine-tune technique. The results of detecting drone in our experiments were around . The combination of drone detection, Dlib correlation tracking algorithm and centroid tracking algorithm effectively detects and tracks the small drone in various complex environments as well as is able to handle multiple target appearances. |
