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西北师范大学 物理与电子工程学院, 甘肃 兰州 730070
Received:16 November 2018,
Accepted:26 February 2019,
Published:05 June 2019
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Yong-jie MA, Xiao-feng SONG. Vehicle flow detection based on YOLO and embedded system[J]. Chinese journal of liquid crystals and displays, 2019, 34(6): 613-618.
Yong-jie MA, Xiao-feng SONG. Vehicle flow detection based on YOLO and embedded system[J]. Chinese journal of liquid crystals and displays, 2019, 34(6): 613-618. DOI: 10.3788/YJYXS20193406.0613.
城市道路普遍存在机动车、非机动车、行人的人车混行路段,车辆目标的准确识别与统计成为视频方法检测混合交通流量的关键问题。本文提出了基于深度学习YOLO(You Only Look Once)的车流量检测算法。用YOLO v2检测道路上移动的目标,对检出目标中的车辆目标进行识别与筛选,设置感兴趣区域,在车辆目标经过感兴趣区域时计数,并用核相关滤波器跟踪车辆,避免车辆重复计数;在ARM上利用该算法实现了混合交通视频中的车流量检测。测试结果表明,该方法中车辆的检测、跟踪、计数结果良好,可应用于混合交通中的车流量检测。
For the mixed traffic of motor vehicles
non-motor vehicles and pedestrians in urban roads
the accurate identification and statistics of vehicle targets become the key issues in video detection of mixed traffic flow. A traffic flow detection algorithm based on deep learning algorithm YOLO (You Only Look Once) was proposed in this paper. YOLO v2 was used to detect moving targets on the road
the region of interest was set up
the vehicle targets passed through the region of interest were counted
and the vehicles were tracked with the kernel correlation filter to avoid repeated counting. The traffic flow detection in mixed traffic video was realized by using this algorithm on ARM. The test results show that the results of vehicle detection
tracking and counting by this method are good and can be applied to the detection of vehicle flow in mixed traffic.
KRIZHEVSKY A, SUTSKEVER I, HINTON G E.ImageNet classification with deep convolutional neural networks[C]// International Conference on Neural Information Processing Systems, California: ACM, 2012: 1097-1105.
GIRSHICK R, DONAHUE J, DARRELL T, et al . Rich feature hierarchies for accurate object detection and semantic segmentation[C]// Proceedings of 2014 IEEE Conference on Computer Vision and Pattern Recognition. Columbus, OH, USA: IEEE, 2013: 580-587.
REDMON J, DIVVALA S, GIRSHICK R, et al . You only look once: unified, real-time object detection[C]// Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition , Las Vegas, NV, USA: IEEE, 2016: 779-788.
REDMON J, FARHADI A. YOLO9000: better, faster, stronger[C]// Proceedings of 2017 IEEE Conference on Computer Vision and Pattern Recognition , Honolulu , HI, USA: IEEE, 2017: 6517-6525.
REDMON J, FARHADI A. YOLOv3: an incremental improvement[J]. arXiv: 1804.02767, 2018.
TIJTGAT N, VAN RANST W, VOLCKAERT B, et al . Embedded real-time object detection for a UAV warning system[C]// Proceedings of 2017 IEEE International Conference on Computer Vision . Venice, Italy: IEEE, 2017: 2110-2118.
SHAFIEE M J, CHYWL B, LI F, et al . Fast YOLO: a fast you only look once system for real-time embedded object detection in video[J]. arXiv: 1709.05943, 2017.
薛月菊, 黄宁, 涂淑琴, 等.未成熟芒果的改进YOLOv2识别方法[J].农业工程学报, 2018, 34(7):173-179.
XUE Y J, HUANG N, TU S Q, et al . Immature mango detection based on improved YOLOv2[J]. Transactions of the Chinese Society of Agricultural Engineering , 2018, 34(7):173-179. (in Chinese)
丁明宇, 牛玉磊, 卢志武, 等.基于深度学习的图片中商品参数识别方法[J].软件学报, 2018, 29(4):1039-1048.
DING M Y, NIU Y L, LU Z W, et al . Deep learning for parameter recognition in commodity images[J]. Journal of Software , 2018, 29(4):1039-1048. (in Chinese)
周云成, 许童羽, 邓寒冰, 等.基于面向通道分组卷积网络的番茄主要器官实时识别[J].农业工程学报, 2018, 34(10):153-162.
ZHOU Y C, XU T Y, DENG H B, et al . Real-time recognition of main organs in tomato based on channel wise group convolutional network[J]. Transactions of the Chinese Society of Agricultural Engineering , 2018, 34(10):153-162. (in Chinese)
HENRIQUES J F, CASEIRO R, MARTINS P, et al . High-speed tracking with kernelized correlation filters[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence , 2015, 37(3):583-596.
杨德东, 蔡玉柱, 毛宁, 等.采用核相关滤波器的长期目标跟踪[J].光学精密工程, 2016, 24(8):2037-2049.
YANG D D, CAI Y Z, MAO N, et al . Long-term object tracking based on kernelized correlation filters[J]. Optics and Precision Engineering , 2016, 24(8):2037-2049. (in Chinese)
潘振福, 朱永利, 周国亮.基于改进核相关滤波器的PTZ摄像机控制方法[J].机器人, 2016, 38(4):420-427.
PAN Z F, ZHU Y L, ZHOU G L. The PTZ camera control method based on the improvedkernelized correlation filter[J]. Robot , 2016, 38(4):420-427. (in Chinese)
马永杰, 宋晓凤, 李雪燕, 等.基于嵌入式车流量实时检测算法研究与实现[J].液晶与显示, 2018, 33(9):787-792.
MA Y J, SONG X F, LI X Y, et al . Research and implementation of real-time vehicle flow detection algorithm based on embedded system[J]. Chinese Journal of Liquid Crystals and Displays , 2018, 33(9):787-792. (in Chinese)
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