Challenges of Computer Vision for Commercial Unmanned Aerial Vehicle Detection

Abstract

The study aims to analyze the existing computer vision techniques for commercial drone detection to identify their advantages, disadvantages, and determine the best approaches in different application scenarios. The research methodology used synthesis methods to explore and propose combinations of techniques based on an analysis of the methodology and results of other works in the literature. It employed algorithms and sensor data analysis to assess the effectiveness of detection methods, and deduction to formulate hypotheses and conclusions based on data and theories. The main research results include the development of computer vision methods for detecting commercial drones, identifying their visual detectability at different altitudes, analyzing different object detection methods, and evaluating the applicability of these methods for commercial applications. In addition, the study identified the advantages and disadvantages of applying computer vision to commercial drone detection and offered recommendations for further research and practical implementation. The practical value of this study is to improve the detection systems of commercial drones, thereby enhancing the safety and efficiency of their use.