Abstract
With the increasing number of drones, the danger of their illegal use has become relevant. This has necessitated the creation of automatic drone protection systems. One of the important tasks solved by these systems is the reliable detection of drones near guarded objects. This problem can be solved using various methods. From the point of view of the price–quality ratio, the use of video cameras for a drone detection is of great interest. However, drone detection using visual information is hampered by the large similarity of drones to other objects, such as birds or airplanes. In addition, drones can reach very high speeds, so detection should be done in real time. This paper addresses the problem of real-time drone detection with high accuracy. We divided the drone detection task into two separate tasks: the detection of moving objects and the classification of the detected object into drone, bird, and background. The moving object detection is based on background subtraction, while classification is performed using a convolutional neural network (CNN). The experimental results showed that the proposed approach can achieve an accuracy comparable to existing approaches at high processing speed. We also concluded that the main limitation of our detector is the dependence of its performance on the presence of a moving background.
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Reference55 articles.
1. Drone Crash at White House Reveals Security Riskshttps://www.usatoday.com/story/news/2015/01/26/drone-crash-secret-service-faa/22352857/
2. Drone Hits Passenger Plane in Canadahttps://money.cnn.com/2017/10/16/technology/drone-passenger-plane-canada/index.html.
3. Gatwick Drone Disruption Cost Airport Just £1.4 mhttps://www.theguardian.com/uk-news/live/2018/dec/21/gatwick-drone-airport-limited-flights-live.
4. https://www.northwestgeorgianews.com/report-trio-planned-to-use-drone-to-to-get-tobacco-phones-to-inmate/article_44c25a12-7d96-11ea-8c97-73fe94e065d4.html
Cited by
84 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献