Flying Object Detection and Classification by Monitoring Using Video Images

In recent years, there has been remarkable development in unmanned aerial vehicle UAVs); certain companies are trying to use the UAV to deliver goods also. Therefore, it is predicted that many such objects will fly over the city, in the near future. This study proposes a system for monitoring objects flying over a city. We use multiple 4K video cameras to capture videos of the flying objects. In this research, we combine background subtraction and a state-of-the-art tracking method, the KCF, for detection and tracking. We use deep learning for classification and the SfM for calculating the 3-dimensional trajectory. A UAV is flown over the inner-city area of Tokyo and videos are captured. The accuracy of each processing is verified, using the videos of objects flying over the city. In each processing, we obtain a certain measure of accuracy; thus, there is a good prospect of creating a system to monitor objects flying, over a city.