FMT Selector: Fourier-Mellin Transformer with High Speed Rotating in Ship Target Detection and Tracking Based on Internet of Things and Wireless Sensor Network

Abstract

The terminal guidance tracking always has high speed rotating and scale changing. It makes a large margin of error in current tracking algorithms, which can transmit wrong position in the wireless sensor networks of the Internet of Things. In this paper, we propose a selector based on Fourier-Mellin transformer, which can accurately track the target with high speed rotating. Firstly we use existing detector to get all proposal target per frame. Then, we use Fourier-Mellin matching to select the best target in the new frame. Our dataset is the ship video which is created by HRSC2016 in rotating. Experimental results show that the accuracy of this method is up to 89.8%. Compared with other traditional tracking algorithms, it has a leap forward. The FMT selector can be applied to the back end of the detector, and it can achieve a feasible effect in the field of terminal guidance tracking.