Target distance measurement method using monocular vision

被引:15
作者
Mao Jiafa [1 ]
Huang Wei [1 ]
Sheng Weiguo [2 ]
机构
[1] Zhejiang Univ Technol, Coll Comp Sci & Technol, Hangzhou 310023, Zhejiang, Peoples R China
[2] Hangzhou Normal Univ, Dept Comp Sci, Hangzhou 311121, Zhejiang, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
position control; computer vision; image sensors; distance measurement; cameras; monocular vision; spatial positioning schemes; nonvision sensors; camera imaging; equivalent focal length; camera resolution; target distance measurement method; machine vision-based location methods; digital signal; SIMULTANEOUS LOCALIZATION;
D O I
10.1049/iet-ipr.2019.1293
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Most existing machine vision-based location methods mainly focus on the spatial positioning schemes using one or two cameras along with non-vision sensors. To achieve an accurate location, both schemes require processing a large amount of data. In this study, the authors propose a novel method, which requires much less amount of data to be processed for measuring target distance using monocular vision. Based on the geometric model of camera imaging, the parameters of the camera (such as camera's focal length and equivalent focal length.), as well as the principle of analogue signal being transformed into a digital signal, the authors derive the relationship among the target distance, field of view, equivalent focal length and camera resolution. Experimental results show that the proposed method can effectively and accurately achieve the target distance measurement.
引用
收藏
页码:3181 / 3187
页数:7
相关论文
共 44 条
  • [11] Depth Estimation From a Single Image Using Deep Learned Phase Coded Mask
    Haim, Harel
    Elmalem, Shay
    Giryes, Raja
    Bronstein, Alex M.
    Marom, Emanuel
    [J]. IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING, 2018, 4 (03) : 298 - 310
  • [12] Learning Depth From Single Images With Deep Neural Network Embedding Focal Length
    He, Lei
    Wang, Guanghui
    Hu, Zhanyi
    [J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2018, 27 (09) : 4676 - 4689
  • [13] Neural network-based adaptive tracking control of mobile robots in the presence of wheel slip and external disturbance force
    Hoang, Ngoc-Bach
    Kang, Hee-Jun
    [J]. NEUROCOMPUTING, 2016, 188 : 12 - 22
  • [14] 3D depth information extraction with omni-directional camera
    Jia, Tong
    Shi, Yan
    Zhou, ZhongXuan
    Chen, DongYue
    [J]. INFORMATION PROCESSING LETTERS, 2015, 115 (02) : 285 - 291
  • [15] Kong Ling-fu, 2009, Computer Integrated Manufacturing Systems, V15, P1633
  • [16] A new technique to gather 3-D spatial information using a single camera
    Laurel, BJ
    Laurel, CJ
    Brown, JA
    Gregory, RS
    [J]. JOURNAL OF FISH BIOLOGY, 2005, 66 (02) : 429 - 441
  • [17] A Monocular Vision Sensor-Based Efficient SLAM Method for Indoor Service Robots
    Lee, Tae-jae
    Kim, Chul-hong
    Cho, Dong-il Dan
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2019, 66 (01) : 318 - 328
  • [18] A monocular vision system for online pose measurement of a 3RRR planar parallel manipulator
    Li, Hai
    Zhang, Xian-min
    Zeng, Lei
    Huang, Yan-jiang
    [J]. JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2018, 92 (01) : 3 - 17
  • [19] A comprehensive review of current local features for computer vision
    Li, Jing
    Allinson, Nigel M.
    [J]. NEUROCOMPUTING, 2008, 71 (10-12) : 1771 - 1787
  • [20] Research on the calibration technology of an underwater camera based on equivalent focal length
    Li, Sheng-Qian
    Xie, Xiao-Peng
    Zhuang, Yong-Jun
    [J]. MEASUREMENT, 2018, 122 : 275 - 283