Pedestrian detection and route tracking from aerial view of quad-rotor UAVs
DOI:
Author:
Affiliation:

University of Electronic Science and Technology of China, School of Information and Communication Engineering, Chengdu, Sichuan, 611731

Clc Number:

TP183

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Aiming at the advantages of UAVs with wider shooting view and more flexible shooting angles and in order to realize and quantitatively evaluate the application of existing object detection algorithms in pedestrian detection and route tracking from aerial view, this paper constructed a pedestrian detection and routes tracking algorithm from aerial shooting view of quad-rotor UAVs. The algorithm adopts YOLOv5 as object detection model, and uses video data collected in practical situation as test data. Model YOLOv5 is trained at first, then through the statistics of the detectin results, the parameters of UAVs’ video-shooting such as horizontal distance, vertical height and pedestrians’ postures during UAVs’ shooting are quantitatively analyzed and verified. Based on the anchor frame, the route curves of pedestrians' movement is outlined to realize path tracking. The results of pedestrian detection and trajectory tracking demonstrate that the algorithm has certain cut-off height of 15 to 20 meters, cut-off angle of arctan3 to arctan4 and cut-off distance of about 20 meters in practical application, but it is less affected by pedestrian postures. Compared with other conventional object detection algorithms, this algorithm has better performance and is expected to be used in situations where the shooting angle is required to be broader and the shooting position is required to be more flexible. In addition, the cut-off height and cut-off distance requirements of the algorithm, calculated by this paper in pedestrian detection quantitatively, has guiding significance for the practical application of the algorithm to carry out UAV detection or rescue.

    Reference
    Related
    Cited by
Get Citation
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:
  • Revised:
  • Adopted:
  • Online: May 07,2024
  • Published: