High-Precision Binocular Camera Calibration Based on Super-Resolution Corner Point Detection Algorithm

Ting Sun; Na Chen; Ran Meng; Qian Long; Qiwei Xie

doi:10.3788/LOP223305

Laser & Optoelectronics Progress, Volume. 60, Issue 8, 0811029(2023)

High-Precision Binocular Camera Calibration Based on Super-Resolution Corner Point Detection Algorithm

Ting Sun^1,2, Na Chen¹, Ran Meng², Qian Long^3、*, and Qiwei Xie⁴

Author Affiliations

¹School of Mathematics and Statistics, Hubei University, Wuhan 430062, Hubei, China

²Beijing Smarter Eye Technology Co., Ltd., Beijing 100023, China

³Yunnan Observatories, Chinese Academy of Sciences, Kunming 650000, Yunnan, China

⁴Research Base of Beijing Modern Manufacturing Development, Beijing University of Technology, Beijing 100124, China

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Figures & Tables(16)

Fig. 1. Principles of binocular stereo vision imaging

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Fig. 2. MASP algorithm framework structure diagram

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Fig. 3. MANet overall framework

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Fig. 4. MAConv framework

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Fig. 5. Reconstruct image frame

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Fig. 6. Corner detection frame

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Fig. 7. Visualization of sub-pixel corner detection at different resolutions. (a) 2× resolution; (b) 3× resolution; (c) 4× resolution

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Fig. 8. Low-resolution checkerboard calibration board left and right camera images. (a)(c) Left images; (b)(d) right images

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Fig. 9. Calibration plate diagram at a distance of 3-14 m

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Table 1. Comparison of accuracy ratio of corner detection under different resolution

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Table 1. Comparison of accuracy ratio of corner detection under different resolution

Scale factor	$R_{d e}$					$R_{d}$
Scale factor	$E_{e r r o r}$ =0-0.2 pixel	$E_{e r r o r}$ =0.2-0.4 pixel	$E_{e r r o r}$ =0.4-0.6 pixel	$E_{e r r o r}$ =0.6-0.8 pixel	$E_{e r r o r}$ =0.8-0.9 pixel	$R_{d}$
$\times$ 2	0.4982	0.4175	0.0788	0.0053	0.0000	0.9738
$\times$ 3	0.4937	0.4165	0.0789	0.0089	0.0017	0.9720
$\times$ 4	0.4046	0.4334	0.1312	0.0251	0.0053	0.9703

Table 2. Comparison of different corner detection algorithms

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Table 2. Comparison of different corner detection algorithms

Algorithm	$R_{d e}$
Algorithm	$E_{e r r o r}$ =0-0.2 pixel	$E_{e r r o r}$ =0.2-0.4 pixel	$E_{e r r o r}$ =0.4-0.6 pixel	$E_{e r r o r}$ =0.6-0.8 pixel	$E_{e r r o r}$ =0.8-0.9 pixel	$E_{e r r o r}$ =0.9-2 pixel	$R_{d}$	$E_{m d}$ /pixel
SuperPoint	0.0960	0.3352	0.3333	0.1920	0.0433	0.0000	0.9267	0.34
Harris	0.0059	0.0633	0.1920	0.3485	0.1485	0.2415	0.8813	0.64
MASP	0.4982	0.4175	0.0788	0.0053	0.0000	0.0000	0.9738	0.21

Table 3. Calibration parameters obtained by Harris corner point detection

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Table 3. Calibration parameters obtained by Harris corner point detection

Binocular camera parameter	Left camera parameter	Right camera parameter
$R_{x}$ =0.0011	$k_{1}$ =-0.51	$k_{1}$ =-0.52
$R_{y}$ =-0.0006	$k_{2}$ =-0.68	$k_{2}$ =-0.22
$R_{z}$ =0.0149	$f_{x}$ =967.70	$f_{x}$ =964.79
$T_{x}$ =-120.5738	$f_{y}$ =965.78	$f_{y}$ =962.77
$T_{y}$ =-0.9858	$C_{x}$ =318.27	$C_{x}$ =317.93
$T_{z}$ =-8.5164	$C_{y}$ =178.92	$C_{y}$ =180.30

Table 4. Calibration parameters obtained by 2× resolution MASP corner point detection

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Table 4. Calibration parameters obtained by 2× resolution MASP corner point detection

Binocular camera parameter	Left camera parameter	Right camera parameter
$R_{x}$ =0.0010	$k_{1}$ =-0.55	$k_{1}$ =-0.51
$R_{y}$ =0.0002	$k_{2}$ =0.42	$k_{2}$ =-0.40
$R_{z}$ =0.0149	$f_{x}$ =1932.87	$f_{x}$ =1928.53
$T_{x}$ =-120.4570	$f_{y}$ =1929.41	$f_{y}$ =1925.31
$T_{y}$ =-1.1657	$C_{x}$ =637.05	$C_{x}$ =637.41
$T_{z}$ =-4.4702	$C_{y}$ =356.87	$C_{y}$ =359.43

Table 5. Calibration parameters obtained by 3× resolution MASP corner point detection

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Table 5. Calibration parameters obtained by 3× resolution MASP corner point detection

Binocular camera parameter	Left camera parameter	Right camera parameter
$R_{x}$ =0.0012	$k_{1}$ =-0.56	$k_{1}$ =-0.52
$R_{y}$ =0.0003	$k_{2}$ =0.43	$k_{2}$ =-0.21
$R_{z}$ =0.01486	$f_{x}$ =1934.35	$f_{x}$ =1932.74
$T_{x}$ =-120.6524	$f_{y}$ =1932.60	$f_{y}$ =1925.31
$T_{y}$ =-1.0536	$C_{x}$ =634.11	$C_{x}$ =631.59
$T_{z}$ =-4.3653	$C_{y}$ =358.47	$C_{y}$ =361.42

Table 6. Calibration parameters obtained by 4× resolution MASP corner point detection

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Table 6. Calibration parameters obtained by 4× resolution MASP corner point detection

Binocular camera parameter	Left camera parameter	Right camera parameter
$R_{x}$ =0.0014	$k_{1}$ =-0.54	$k_{1}$ =-0.51
$R_{y}$ =0.0004	$k_{2}$ =0.00	$k_{2}$ =-0.53
$R_{z}$ =0.01485	$f_{x}$ =1932.99	$f_{x}$ =1922.54
$T_{x}$ =-120.4545	$f_{y}$ =1930.37	$f_{y}$ =1919.69
$T_{y}$ =-1.3821	$C_{x}$ =636.61	$C_{x}$ =633.80
$T_{z}$ =-12.1748	$C_{y}$ =358.22	$C_{y}$ =361.84

Table 7. Error rate of ranging after correcting the image with different internal and external parameters

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Table 7. Error rate of ranging after correcting the image with different internal and external parameters

Method	$R_{e r r o r}$
Method	$M c_{M}$ $M r_{H}$	$M c_{M}$ $M r_{M}$	$M c_{H}$ $M r_{H}$	$M c_{H}$ $M r_{M}$
Average error rate	0.0340	0.0193	0.0308	0.0297
D3	0.0076	0.0073	0.0113	0.0112
D4	0.0083	0.0074	0.0100	0.0100
D5	0.0114	0.0099	0.0149	0.0154
D6	0.0190	0.0139	0.0217	0.0211
D7	0.0169	0.0149	0.0248	0.0244
D8	0.0266	0.0153	0.0377	0.0341
D9	0.0273	0.0297	0.0339	0.0312
D10	0.0341	0.0199	0.0390	0.0360
D11	0.0359	0.0146	0.0531	0.0557
D12	0.0384	0.0293	0.0544	0.0396
D13	0.0583	0.0299	0.0384	0.0367
D14	0.1250	0.0399		0.0413

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Ting Sun, Na Chen, Ran Meng, Qian Long, Qiwei Xie. High-Precision Binocular Camera Calibration Based on Super-Resolution Corner Point Detection Algorithm[J]. Laser & Optoelectronics Progress, 2023, 60(8): 0811029

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Paper Information

Category: Imaging Systems

Received: Dec. 12, 2022

Accepted: Feb. 6, 2023

Published Online: Apr. 13, 2023

The Author Email: Long Qian (longqian@ynao.ac.cn)

DOI:10.3788/LOP223305

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology