Laser & Optoelectronics Progress, Volume. 58, Issue 6, 615005(2021)

Real-Time Monocular Depth Estimation Method Based on Perspective N-Point model

Guo Keyou1、*, Yang Min1, Zhang Mo2, Guo Xiaoli1, and Li Xue1
Author Affiliations
  • 1School of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, China
  • 2Research Institute of Highway Ministry of Transport, Beijing 100088, China
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    Figures & Tables(11)
    Specific implementation process of our method
    Flow chart of the camera calibration
    Flow chart of the license plate location algorithm
    License plate images obtained through preliminary screening
    Schematic diagram of the homography model
    Simplified geometry model of road scene. (a) Depth geometry model; (b) road model of the vehicle-mounted camera and imaging diagram; (c) principle of the vertical imaging ; (d) principle of the horizontal imaging
    Model of the quadrilateral space object point coordinate system
    Depth measurement result
    Application effect diagram of our method on video sequence. (a) Video sequence effect chart1; (b) video sequence effect chart2
    • Table 1. Combination characteristic license plate data selected by SVM

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      Table 1. Combination characteristic license plate data selected by SVM

      Experiment methodBest parameter set(Cp,g)Experience risk/%Confidence risk/%Structured risk/%Training time/s
      PSO(1.3204,0.01)00.47570.475712364.9101
      GA(1.0053,0.04673)0004521.0216
    • Table 2. Basic information of the objects

      View table

      Table 2. Basic information of the objects

      Object pointTrue depth information/mImage coordinates
      Object point15.5(1220,751)
      Object point26.0(1260,753)
      Object point36.5(1289,759)
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    Guo Keyou, Yang Min, Zhang Mo, Guo Xiaoli, Li Xue. Real-Time Monocular Depth Estimation Method Based on Perspective N-Point model[J]. Laser & Optoelectronics Progress, 2021, 58(6): 615005

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    Paper Information

    Category: Machine Vision

    Received: Jul. 24, 2020

    Accepted: --

    Published Online: Mar. 11, 2021

    The Author Email: Keyou Guo (guoky@th.btbu.edu.cn)

    DOI:10.3788/LOP202158.0615005

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