一种基于YOLOv3的共享单车违规停放检测方法

doi:10.19678/j.issn.1000-3428.0054915

计算机工程 ›› 2019, Vol. 45 ›› Issue (12): 237-242. doi: 10.19678/j.issn.1000-3428.0054915

一种基于YOLOv3的共享单车违规停放检测方法

盛宜华¹, 武友新¹, 姚磊岳²

1. 南昌大学信息工程学院, 南昌 330031;
2. 江西科技学院协同创新中心, 南昌 330098

收稿日期:2019-05-14 修回日期:2019-06-25 发布日期:2019-07-12
作者简介:盛宜华(1994-),男,硕士研究生,主研方向为计算机视觉、数据挖掘、人工智能;武友新、姚磊岳,教授。
基金资助:
江西省科技厅科技计划专项"基于自然语音交互模式的行车安全辅助系统"（20171BBE50060）；南昌市科技局科技计划项目"基于移动互联网的‘人-车’语音交互系统"（2016-ZCJHCXY-013）。

An Illegal Parking Detection Approach for Shared Bicycles Based on YOLOv3

SHENG Yihua¹, WU Youxin¹, YAO Leiyue²

1. School of Information Engineering, Nanchang University, Nanchang 330031, China;
2. Center of Collaboration and Innovation, Jiangxi University of Technology, Nanchang 330098, China

Received:2019-05-14 Revised:2019-06-25 Published:2019-07-12

摘要/Abstract

摘要： 为解决共享单车随意停放给交通管理带来的困难，提出一种基于计算机视觉的共享单车违规停放检测方法。通过多尺度检测训练以及k-means维度聚类改进YOLOv3网络，在此基础上获取共享单车在图片上的特征矩阵，根据特征矩阵计算当前场景下共享单车的运行状态并进行状态统计。在交通监控视频数据集上的测试结果表明，该方法的检测准确率达到87%以上，能够实现共享单车违规停放的有效检测并给出实时预警。

关键词: 共享单车, 停放检测, YOLOv3网络, 计算机视觉, 状态统计

Abstract: To solve the transportation management difficulties caused by the random parking of shared bicycles,this paper proposes an illegal parking detection method based on computer vision for shared bicycles.The method uses multi-scale detection training and k-means dimensional clustering to improve YOLOv3 network,and accordingly obtains the feature matrix of the shared bicycle on the image.Based on the obtained feature matrix,the running state of the target shared bicycle in a certain scenario can be computed for statistics.Testing results on the dataset of transportation monitoring videos show that the detection accuracy rate of the proposed method is above 87%,which means it can effectively detect illegal parking of shared bicycles and give real-time alarms.

Key words: shared bicycles, parking detection, YOLOv3 network, computer vision, state statistics

中图分类号:

TP391

盛宜华, 武友新, 姚磊岳. 一种基于YOLOv3的共享单车违规停放检测方法[J]. 计算机工程, 2019, 45(12): 237-242.

SHENG Yihua, WU Youxin, YAO Leiyue. An Illegal Parking Detection Approach for Shared Bicycles Based on YOLOv3[J]. Computer Engineering, 2019, 45(12): 237-242.

https://www.ecice06.com/CN/Y2019/V45/I12/237

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参考文献

[1] GUO Peng,LING Xiangzhi,HUANG Yi,et al.Shared bicycles:collaborative governance in internet technology and public services[J].Journal of Public Management,2017,14(3):1-10.(in Chinese)郭鹏,林祥枝,黄艺,等.共享单车:互联网技术与公共服务中的协同治理[J].公共管理学报,2017,14(3):1-10.
[2] CHENG Rong,ZHANG Mengmeng,YU Xuemei,et al.Research and analysis on the parking situation of shared bikes in Beijing[J].Technology Wind,2018(23):205-206.(in Chinese)程荣,张萌萌,于雪梅,等.北京市共享单车停放现状调研分析[J].科技风,2018(23):205-206.
[3] GRANLUND G H,KNUTSSON H.Signal processing for computer vision[M].Berlin,Germany:Springer,2013:20-35.
[4] LAGANIōRE R.OpenCV computer vision application programming cookbook[M].Birmingham,UK:Packt Publishing,2014:15-35.
[5] QUI Zhijun,YAO Danya,ZHANG Yi,et al.The study of the detection of pedestrian and bicycle using image processing[C]//Proceedings of 2003 IEEE International Conference on Intelligent Transportation Systems.Washington D.C.,USA:IEEE Press,2003:340-345.
[6] ZHANG Jun,ZHU Zhiqiang,LIU Ping,et al.Detection of contours of wheels based on improved codebook[C]//Proceedings of International Conference on Machine Learning and Cybernetics.Washington D.C.,USA:IEEE Press,2014:510-515.
[7] LEE Y,KIM T,LEE S,et al.Spatial regions periodicity based detection of two-wheelers using histogram of oriented gradients[J].International Journal of Multimedia and Ubiquitous Engineering,2015,10(4):325-336.
[8] JUNG H,EHARA Y,TAN J K,et al.Detection of a bicycle in video images using MSC-HOG feature[J].International Journal of Innovative Computing,Information and Control,2014,10(2):521-533.
[9] GIRSHICK R.Fast R-CNN[C]//Proceedings of IEEE International Conference on Computer Vision.Washington D.C.,USA:IEEE Press,2015:1440-1448.
[10] REN Shaoqing,HE Kaiming,GIRSHICK R,et al.Faster R-CNN:towards real-time object detection with region proposal networks[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2017,39(6):91-99.
[11] REDMON J,DIVVALA S,GIRSHICK R,et al.You only look once:unified,real-time object detection[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2016:779-788.
[12] REDMON J,FARHADI A.YOLO9000:better,faster,stronger[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2017:7263-7271.
[13] REDMON J,FARHADI A.YOLOv3:an incremental improvement[EB/OL].[2019-05-01].https://arxiv.org/pdf/1804.02767.pdf.
[14] ZHANG Guoping,ZHOU Gaiyun,MA Li.Multi-target tracking based on key-point modeling and weakly supervised appearance updating[J].Computer Engineering,2016,42(8):261-265.(in Chinese)张国平,周改云,马丽.基于关键点建模与弱监督外观更新的多目标跟踪[J].计算机工程,2016,42(8):261-265.
[15] HASSAN W,BIRCH P,YOUNG R,et al.Real-time occlusion tolerant detection of illegally parked vehicles[J].International Journal of Control,Automation and Systems,2012,10(5):972-981.
[16] BOCK F,LIU J,SESTER M.Learning on street parking maps from position information of parked vehicles[M].Berlin,Germany:Springer,2016:20-50.
[17] HUANG Kaiqi,CHEN Xiaotang,KANG Yunfeng,et al.Intelligent visual surveillance:a review[J].Chinese Journal of Computers,2015,20(6):1093-1118.(in Chinese)黄凯奇,陈晓棠,康运锋,等.智能视频监控技术综述[J].计算机学报,2015,20(6):1093-1118.
[18] MADDALENA L,PETROSINO A.Stopped object detection by learning foreground model in videos[J].IEEE Transactions on Neural Networks and Learning Systems,2013,24(5):723-735.
[19] LEE J T,RYOO M S,RILEY M,et al.Real-time detection of illegally parked vehicles using 1-D transformation[C]//Proceedings of 2007 IEEE Conference on Advanced Video and Signal Based Surveillance.Washington D.C.,USA:IEEE Press,2007:254-259.
[20] XIE Xuemei,WANG Chenye,CHEN Shu,et al.Real-time illegal parking detection system based on deep learning[C]//Proceedings of 2017 International Conference on Deep Learning Technologies.New York,USA:ACM Press,2017:23-27.
[21] EVERINGHAM M,VAN GOOL L,WILLIAMS C K I,et al.The pascal visual object classes (2007) challenge[J].International Journal of Computer Vision,2010,88(2):303-338.
[22] PONT-TUSET J,VAN GOOL L.Boosting object proposals:from pascal to COCO[C]//Proceedings of IEEE International Conference on Computer Vision.Washington D.C.,USA:IEEE Press,2015:1546-1554.
[23] DALAL N,TRIGGS B.Histograms of oriented gradients for human detection[C]//Proceedings of International Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2005:886-893.

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