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The AGVS dataset series and the development of computer vision algorithms for airport ground surveillance aim to create intelligent airport applications that enhance operational efficiency and safety. Common applications include airport augmented reality, visual conflict warnings, and visual docking guidance, all leveraging algorithms for segmentation, recognition, and tracking. In this chapter, we will use the Airport Panoramic Enhanced Surveillance system (APES), designed by our team, as a case study to illustrate the design methodology for intelligent airport applications. The APES system, collaboratively developed by the University of Electronic Science and Technology of China and the Second Research Institute of the Civil Aviation Administration of China, has been implemented in numerous Chinese airports.

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Applications

  • 章节

  • 发表日期：

    2025年

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  • Xiang Zhang,
  • Honggang Wu,
  • Guoqiang Wang,
  • Jian Cheng

摘要

The AGVS dataset series and the development of computer vision algorithms for airport ground surveillance aim to create intelligent airport applications that enhance operational efficiency and safety. Common applications include airport augmented reality, visual conflict warnings, and visual docking guidance, all leveraging algorithms for segmentation, recognition, and tracking. In this chapter, we will use the Airport Panoramic Enhanced Surveillance system (APES), designed by our team, as a case study to illustrate the design methodology for intelligent airport applications. The APES system, collaboratively developed by the University of Electronic Science and Technology of China and the Second Research Institute of the Civil Aviation Administration of China, has been implemented in numerous Chinese airports.