In this paper, a video intelligent monitoring and tracking system is designed based on Computer Vision algorithm. The system is developed and implemented with OpenCV computer vision library, Visual Studio and MFC framework. Firstly, the overall framework of the system is designed, and the second is to analyze the preprocessing of video data. Then, the target is extracted by the Gaussian mixture background difference method, and the target is separated from the background by thresholding. Then, the target is tracked by Camshift and Kalman filters and an alarm prompt is issued. The final system implementation results show that the moving target extraction based on the Gaussian mixture background difference method, and through binary processing, can be accurately and reliably separated from the background, and the target detection effect is remarkable; the alarm mechanism can be triggered accurately and timely, and the alarm prompt information can be issued.

Yucao Tang. Design of UAV Cooperative Target Tracking System Based on Computer Vision Algorithm. Academic Journal of Engineering and Technology Science (2022) Vol. 5, Issue 4: 48-54. https://doi.org/10.25236/AJETS.2022.050409.

[1] Xiao Guideng. Research on video intelligent monitoring and tracking system based on computer vision algorithm [J]. Automation Technology and Application, 2021, 40(6):5.

[2] Xu Zhengshuo. Thoughts on automatic navigation of unmanned aerial vehicles based on computer vision technology [J]. 2022(3).

[3] Li Yuxia, He Lei, Xu Yongxin. Design of teaching experimental platform for "Introduction to Remote Sensing of UAVs" based on image recognition [J]. 2022(5).

[4] Xu Bo. Research on video target tracking based on deep learning [D]. Dalian University of Technology, 2020.

[5] Zhang Haifeng. Design of high-precision differential positioning UAV system based on RTK [J]. Surveying and Mapping and Spatial Geographic Information, 2022, 45(2):4.

[6] Yu Xiaowen, Tang Tao, Zou Yiwei. Construction of an intelligent monitoring system for drilling operations based on computer vision technology [J]. China Petroleum and Chemical Standards and Quality, 2021, 41(21):2.

[7] Tan Jianhao, Zhang Siyuan, Wang Yaonan, et al. A UAV target tracking method and system based on color histogram similarity: CN110766723A[P]. 2020.

[8] Zhang Yu. ROS-based UAV target detection and visual positioning system [D]. Shandong University, 2020.

[9] Peng Cong, Chen Li. A system and method for high-altitude parabolic detection, tracking and warning based on computer vision: CN112800953A[P]. 2021.

[10] Xin Shaou, Chen Ke, Song Zhenlin, et al. Multi-UAV cooperative target tracking algorithm based on pure orientation [J]. Electronic Design Engineering, 2021, 29(24):6.