Journal of Computer and Communications, 2018, 6, 98-107
http://www.scirp.org/journal/jcc
ISSN Online: 2327-5227
ISSN Print: 2327-5219
DOI:
10.4236/jcc.2018.611009 Nov. 19, 2018 98 Journal of Computer and Communications
A Vehicle Detection Method for Aerial Image
Based on YOLO
Junyan Lu
1*
, Chi Ma
2
, Li Li
2
, Xiaoyan Xing
2
, Yong Zhang
2
, Zhigang Wang
2
, Jiuwei Xu
2
1
Chang Guang Satellite Technology Co., Ltd., Changchun, China
2
Department of Transportation of Jilin Province, Changchun, China
Abstract
With the
application of UAVs in intelligent transportation systems, vehicle
detection for aerial images has become a key engineering technology and has
academic research significance. In this paper, a
vehicle detection method for
aerial image based on YOLO deep learning algorithm is presented. The me-
thod integrates an aerial image dataset suitable for YOLO training by
processing three public aerial image datasets. Experiments show that the
training model has a good performance on unknown aerial images, especially
fo
r small objects, rotating objects, as well as compact and dense objects, while
meeting the real-time requirements.
Keywords
Vehicle Detection, Aerial Image, YOLO, VEDAI, COWC, DOTA
1. Introduction
In recent years, with the rapid development of information technology, intelli-
gent transportation systems have become an important way of modern traffic
management and an inevitable trend. As the key technology of intelligent trans-
portation system, vehicle detection is the basis for realizing many important
functions [1], such as measurement and statistics of traffic parameters such as
traffic flow and density, vehicle location and tracking, and traffic data mining,
etc.
At the same time, with the technology maturity and market popularization of
UAV (Unmanned Aerial Vehicle), which has characteristics of being lightweight,
flexible, and cheap, the aerial photography of UAVs in the application of scenes
such as traffic information collection and traffic emergency response reflects a
huge advantage.
How to cite this paper:
Lu, J.Y., Ma, C.,
Li,
L
., Xing, X.Y., Zhang, Y., Wang, Z.G.
and
Xu
, J.W. (2018) A Vehicle Detection Me-
thod for
Aerial Image Based on YOLO
.
Journal of Computer and Communications
,
6
, 98-107.
https:
//doi.org/10.4236/jcc.2018.611009
Received:
August 29, 2018
Accepted:
November 12, 2018
Published:
November 19, 2018
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