The Transactions of the Korean Institute of Electrical Engineers P (전기학회논문지P)

The Korean Institute of Electrical Engineers (대한전기학회)
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The Study of Car Detection on the Highway using YOLOv2 and UAVs

YOLOv2와 무인항공기를 이용한 자동차 탐지에 관한 연구

  • Seo, Chang-Jin (Dept. of Information Security Engineering, Sangmyung University)
  • Received : 2018.02.11
  • Accepted : 2018.02.21
  • Published : 2018.03.01
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Abstract

In this paper, we propose fast object detection method of the cars by applying YOLOv2(You Only Look Once version 2) and UAVs (Unmanned Aerial Vehicles) while on the highway. We operated Darknet, OpenCV, CUDA and Deep Learning Server(SDX-4185) for our simulation environment. YOLOv2 is recently developed fast object detection algorithm that can detect various scale objects as fast speed. YOLOv2 convolution network algorithm allows to calculate probability by one pass evaluation and predicts location of each cars, because object detection process has simple single network. In our result, we could find cars on the highway area as fast speed and we could apply to the real time.

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References

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