A Vehicle Recognition Method Based on Multi-Camera Information

被引:0
|
作者
Zhou, ChunYue [1 ]
Fan, TianYue [1 ]
机构
[1] Beijingjiaotong Univ, Coll Elect Informat Engn, Beijing, Peoples R China
关键词
Deep Learning; Fine-grained identification; vehicle recognition;
D O I
10.23919/chicc.2019.8865148
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Disadvantages of the single-camera-based vehicle identification method include insensitivity to vehicle angle information, vulnerability to occlusion and limited viewing angle of a single camera. In order to solve the above problems, a multi-camera based vehicle identification method is proposed, which detects the vehicle objects in the multi-camera, binds the object bounding box belonging to the same vehicle, and distinguish the vehicle by using the fine-grained identification network combined with the multi-camera information fusion method, Solved the problem of shooting dead ends, insufficient vehicle angle information and occlusion. Experiments show that the proposed method can achieve better recognition accuracy than the single camera recognition method.
引用
收藏
页码:7835 / 7839
页数:5
相关论文
共 50 条
  • [21] Multi-camera multiple vehicle tracking in urban intersections based on multilayer graphs
    Delavarian, Mohadeseh
    Marouzi, Omid Reza
    Hassanpour, Hamid
    Parizi, Reza M.
    Khan, Mohammad S.
    IET INTELLIGENT TRANSPORT SYSTEMS, 2020, 14 (12) : 1673 - 1690
  • [22] Vehicle Localization Based on the Detection of Line Segments from Multi-Camera Images
    Hara, Kosuke
    Saito, Hideo
    JOURNAL OF ROBOTICS AND MECHATRONICS, 2015, 27 (06) : 617 - 626
  • [23] Multi-Camera Vehicle Tracking System Based on Spatial-Temporal Filtering
    Ren, Pengfei
    Lu, Kang
    Yang, Yu
    Yang, Yun
    Sun, Guangze
    Wang, Wei
    Wang, Gang
    Cao, Junliang
    Zhao, Zhifeng
    Liu, Wei
    2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2021, 2021, : 4208 - 4214
  • [24] A Multi-Camera Vehicle Tracking System based on City-Scale Vehicle Re-ID and Spatial-Temporal Information
    Wu, Minghu
    Qian, Yeqiang
    Wang, Chunxiang
    Yang, Ming
    2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2021, 2021, : 4072 - 4081
  • [25] Dynamic view selection for multi-camera action recognition
    Scott Spurlock
    Richard Souvenir
    Machine Vision and Applications, 2016, 27 : 53 - 63
  • [26] Multi-Camera Based Surveillance System
    Behera, Reena Kumari
    Kharade, Pallavi
    Yerva, Suresh
    Dhane, Pranali
    Jain, Ankita
    Kutty, Krishnan
    PROCEEDINGS OF THE 2012 WORLD CONGRESS ON INFORMATION AND COMMUNICATION TECHNOLOGIES, 2012, : 102 - 108
  • [27] Multi-camera calibration method based on a multi-plane stereo target
    Zhang, Jin
    Zhu, Jiang
    Deng, Huaxia
    Chai, Zhiwen
    Ma, Mengchao
    Zhong, Xiang
    APPLIED OPTICS, 2019, 58 (34) : 9353 - 9359
  • [28] Active multi-camera object recognition in presence of occlusion
    Farshidi, F
    Sirouspour, S
    Kirubarajan, T
    2005 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-4, 2005, : 3987 - 3992
  • [29] Dynamic view selection for multi-camera action recognition
    Spurlock, Scott
    Souvenir, Richard
    MACHINE VISION AND APPLICATIONS, 2016, 27 (01) : 53 - 63
  • [30] Synthehicle: Multi-Vehicle Multi-Camera Tracking in Virtual Cities
    Herzog, Fabian
    Chen, Junpeng
    Teepe, Torben
    Gilg, Johannes
    Hoermann, Stefan
    Rigoll, Gerhard
    2023 IEEE/CVF WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION WORKSHOPS (WACVW), 2023, : 1 - 11