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http://dx.doi.org/10.5370/KIEEP.2018.67.4.227

A Study on Pedestrians Tracking using Low Altitude UAV  

Seo, Chang Jin (Dept. of Information Security Engineering, Sangmyung University)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers P / v.67, no.4, 2018 , pp. 227-232 More about this Journal
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.
Keywords
Deep learning; UAV; Target tracking; Object detection; YOLOv3; Kalman filter;
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