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Air-to-Air Visual Detection of Micro-UAVs: An Experimental Evaluation of Deep Learning
- Source :
- IEEE Robotics and Automation Letters. 6:1020-1027
- Publication Year :
- 2021
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2021.
-
Abstract
- This letter studies the problem of air-to-air visual detection of micro unmanned aerial vehicles (UAVs) by monocular cameras. This problem is important for many applications such as vision-based swarming of UAVs, malicious UAV detection, and see-and-avoid systems for UAVs. Although deep learning methods have exhibited superior performance in many object detection tasks, their potential for UAV detection has not been well explored. As the first main contribution of this letter, we present a new dataset, named Det-Fly, which consists of more than 13 000 images of a flying target UAV acquired by another flying UAV. Compared to the existing datasets, the proposed one is more comprehensive in the sense that it covers a wide range of practical scenarios with different background scenes, viewing angles, relative distance, flying altitude, and lightning conditions. The second main contribution of this letter is to present an experimental evaluation of eight representative deep-learning algorithms based on the proposed dataset. To the best of our knowledge, this is the first comprehensive experimental evaluation of deep learning algorithms for the task of visual UAV detection so far. The evaluation results highlight some key challenges in the problem of air-to-air UAV detection and suggest potential ways to develop new algorithms in the future. The dataset is available at https://github.com/Jake-WU/Det-Fly .
- Subjects :
- Control and Optimization
Computer science
Feature extraction
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Biomedical Engineering
ComputerApplications_COMPUTERSINOTHERSYSTEMS
02 engineering and technology
Artificial Intelligence
0202 electrical engineering, electronic engineering, information engineering
Computer vision
Monocular
business.industry
Mechanical Engineering
Deep learning
020208 electrical & electronic engineering
Object detection
Computer Science Applications
Visualization
Human-Computer Interaction
Task (computing)
Control and Systems Engineering
Key (cryptography)
020201 artificial intelligence & image processing
Computer Vision and Pattern Recognition
Artificial intelligence
business
Subjects
Details
- ISSN :
- 23773774
- Volume :
- 6
- Database :
- OpenAIRE
- Journal :
- IEEE Robotics and Automation Letters
- Accession number :
- edsair.doi...........9f097f696cfd5f76c38abf0a907a62c4