Welcome to Francis Academic Press

International Journal of Frontiers in Sociology, 2020, 2(7); doi: 10.25236/IJFS.2020.020707.

Pedestrian Movement Tracking Model in Road Environment Based on UAV Video

Author(s)

Hongxiao Lin and Hui Sun*

Corresponding Author:
Hui Sun
Affiliation(s)

School of Architecture and Fine Art, Dalian University of Technology, Dalian, Liaoning, 116024
*Corresponding author e-mail: dutsunh@163.com

Abstract

The development of science and technology provides new methods for traffic flow survey, the method based on UAV video is one of the widely used methods. UAV is widely used in many kinds of monitoring and measurement due to its advantages. In particular, its flexibility is more applicable to the pedestrian flow survey. However, due to the randomness and uncertainty of pedestrian movement, as well as the many obstacles on the pedestrian road, the UAV cannot accurately track and locate the pedestrian movement, resulting in poor application effect and low measurement accuracy. Based on this, this paper proposes a method of pedestrian tracking model in road environment based on UAV video, which can effectively track and locate pedestrians. The calculation model in this paper is compared with other algorithm models. The results show that the calculation results in this paper are better than other methods, and the accuracy of the model used in this paper can be effectively overcome. In order to overcome the obstacles in the process of tracking, accurate positioning can be carried out to improve the tracking accuracy, which can provide reference for the follow-up research.

Keywords

UAV, Road Environment, Pedestrain, Tracking Model

Cite This Paper

Hongxiao Lin and Hui Sun. Pedestrian Movement Tracking Model in Road Environment Based on UAV Video. International Journal of Frontiers in Sociology (2020), Vol. 2, Issue 7: 58-66. https://doi.org/10.25236/IJFS.2020.020707.

References

[1] Ellenberg A, Kontsos A, Moon F, et al. Bridge deck delamination identification from unmanned aerial vehicle infrared imagery. Automation in Construction, 2016, 72(pt.2):155-165.
[2] Li X B, Wang D S, Lu Q C, et al. Three-dimensional investigation of ozone pollution in the lower troposphere using an unmanned aerial vehicle platform. Environmental Pollution, 2017, 224(MAY):107-116.
[3] Hayat S, Yanmaz E, Muzaffar R. Survey on Unmanned Aerial Vehicle Networks for Civil Applications: A Communications Viewpoint. IEEE Communications Surveys & Tutorials, 2016, 18(4):1-1.
[4] Li, Xiao Hua, and W. Y. Li. "The Research on Intelligent Monitoring Technology of NC Machining Process." Procedia Cirp 56(2016):556-560.
[5] Yang J, Wei F. Design and Research of Ship's Intelligent Monitoring System in Wireless Network Environment. Journal of Coastal Research, 2018, 83:495-498.
[6] Gambi J M, García del Pino, M.L, Gschwindl J, et al. Post-Newtonian equations of motion for LEO debris objects and space-based acquisition, pointing and tracking laser systems. Acta Astronautica, 2017, 141:132-142.
[7] Mosavi M R, Zebarjad R, Moazedi M. Novel Anti-spoofing Methods Based on Discrete Wavelet Transform in the Acquisition and Tracking Stages of Civil GPS Receiver. International Journal of Wireless Information Networks, 2018, 25(4):449-460.
[8] Munck A, Delmas D, Marie-Pierre Audrézet, et al. Optimization of the French cystic fibrosis newborn screening programme by a centralized tracking process:. Journal of Medical Screening, 2018, 25(1):6-12.
[9] B R C A, B F L A, C P M B, et al. Performance of a high-throughput tracking processor implemented on Stratix-V FPGA. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2019, 936:344-345.
[10] Zhong J, Liang S, Xiong Q. Improved receding horizon H∞ temperature spectrum tracking control for Debye media in microwave heating process. Journal of Process Control, 2018, 71:14-24.
[11] Barré, Pierre, St?Ver B C, Müller, Kai F, et al. LeafNet: A computer vision system for automatic plant species identification. Ecological Informatics, 2017:50-56.
[12] Naik N, Raskar R, Hidalgo C A. Cities Are Physical Too: Using Computer Vision to Measure the Quality and Impact of Urban Appearance. American Economic Review, 2016, 106(5):128-132.