Mobile QR Code QR CODE : The Transactions P of the Korean Institute of Electrical Engineers
The Transactions P of the Korean Institute of Electrical Engineers

Korean Journal of Air-Conditioning and Refrigeration Engineering

ISO Journal TitleTrans. P of KIEE
  • Indexed by
    Korea Citation Index(KCI)
Title A Study on Pedestrians Tracking using Low Altitude UAV
Authors 서창진(Chang Jin Seo)
DOI http://doi.org/10.5370/KIEEP.2018.67.4.227
Page pp.227-232
ISSN 1229-800X
Keywords Deep learning ; UAV ; Target tracking ; Object detection ; YOLOv3 ; Kalman filter
Abstract In this paper, we propose a faster object detection and tracking method using Deep Learning, UAV(unmanned aerial vehicle), Kalman filter and YOLO(You Only Look Once)v3 algorithms. The performance of the object tracking system is decided by the performance and the accuracy of object detecting and tracking algorithms. So we applied to the YOLOv3 algorithm which is the best detection algorithm now at our proposed detecting system and also used the Kalman Filter algorithm that uses a variable detection area as the tracking system. In the experiment result, we could find the proposed system is an excellent result more than a fixed area detection system.