北京航空航天大学学报 ›› 2020, Vol. 46 ›› Issue (2): 266-273.doi: 10.13700/j.bh.1001-5965.2019.0234

• 论文 • 上一篇    下一篇

面向低视角场面监视的移动目标速度测量

张天慈1, 丁萌2, 钱小燕2, 左洪福2   

  1. 1. 南京林业大学 汽车与交通工程学院, 南京 210037;
    2. 南京航空航天大学 民航学院, 南京 211106
  • 收稿日期:2019-05-18 发布日期:2020-03-11
  • 通讯作者: 张天慈 E-mail:tczhang@njfu.edu.cn
  • 作者简介:张天慈,男,博士,讲师。主要研究方向:智能交通与新航行系统;丁萌,男,博士,副教授,硕士生导师。主要研究方向:机场场面监控,无人机导航、制导与控制,民用飞机航电系统适航技术;钱小燕,女,博士,副教授,硕士生导师。主要研究方向:智能交通、机场场面监视技术、图像处理与分析。
  • 基金资助:
    国家自然科学基金委员会-中国民用航空局民航联合研究基金(U1633105);国家自然科学基金(61803199);航空科学基金(20170752008);江苏省高等学校自然科学研究面上项目(19KJB580013)

Moving object speed measurement for low-camera-angle surface surveillance

ZHANG Tianci1, DING Meng2, QIAN Xiaoyan2, ZUO Hongfu2   

  1. 1. College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China;
    2. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
  • Received:2019-05-18 Published:2020-03-11
  • Supported by:
    Joint Research Funds of National Natural Science Foundation of China and Civil Aviation Administration of China (U1633105); National Natural Science Foundation of China (61803199); Aeronautical Science Foundation of China (20170752008); Natural Science Foundation of Jiangsu Higher Education Institutions of China (19KJB580013)

摘要: 为构建有效的机场场面视觉监视系统,提出了一种基于特征点持续跟踪与分析的移动目标速度测量方法。首先,利用场面几何特征对摄像机进行标定;然后,基于光流场对图像运动区域的特征点进行持续跟踪,在此基础上通过特征点轨迹聚类区分不同移动目标;最后,根据特征点高度与运动距离完成速度测量。所提方法能够利用机场场面摄像机获取的低视角单目视频图像,对移动目标的运动速度进行准确测量。基于广州白云国际机场的场面运行视频进行了仿真分析,验证了所提方法在低视角速度测量方面的可行性与优势。

关键词: 机场场面监视, 低视角, 轨迹聚类, 速度测量, 标定

Abstract: To build an effective airport surface visual surveillance system, a moving object speed measurement method based on long-term feature point tracking and analysis is proposed. First, the surveillance camera is calibrated using geographic features on the airport surface. Then, the feature points in motion regions of the images are continuously tracked via optical flow fields. On this basis, different moving objects are identified by clustering the feature point trajectories. Finally, the speeds of the moving objects are measured according to the heights and moving distances of the feature points. The proposed method can accurately measure the object moving speeds using low-camera-angle monocular video images obtained by cameras installed on the airport surface. Simulation studies are conducted based on the surface operation videos of Guangzhou Baiyun International Airport, which verify the feasibility and advantages of the proposed method for low-camera-angle speed measurement.

Key words: airport surface surveillance, low camera angle, trajectory clustering, speed measurement, calibration

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