Checkerboard Corner Detection Algorithm for Calibration of Focused Plenoptic Camera

Qingsong Liu; Xiaofang Xie; Xuanzhe Zhang; Yu Tian; Jun Li; Yan Wang; Xiaojun Xu

doi:10.3788/AOS202040.1415002

Acta Optica Sinica, Volume. 40, Issue 14, 1415002(2020)

Checkerboard Corner Detection Algorithm for Calibration of Focused Plenoptic Camera

Qingsong Liu^1,2, Xiaofang Xie^1、*, Xuanzhe Zhang², Yu Tian³, Jun Li², Yan Wang², and Xiaojun Xu²

Author Affiliations

¹Naval Aeronautical University, Yantai, Shandong 264001, China

²College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha, Hunan 410073, China

³College of Computer, National University of Defense Technology, Changsha, Hunan 410073, China

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Figures & Tables(11)

Fig. 1. Camera imaging model. (a) Imaging diagram of main lens; (b) imaging diagram of micro-lenses

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Fig. 2. Corner detection results. (a) Initial corner detection result; (b) result after removal of corners on edges of micro-lenses; (c) candidate corners fitted by RANSAC algorithm; (d) projected corners after optimization

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Fig. 3. Examples of corner detection results. (a) Case with image noise; (b) case with image suffering from large lens distortion; (c) case with multiple corners in one micro-image; (d) case with missed detection

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Fig. 4. Examples of images used in simulated calibration

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Fig. 5. Experimental device and principle diagram of distance measurement. (a) Experiment platform; (b) relative distance

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Fig. 6. Reconstruction results of corners. (a) Our result; (b) result from Ref. [17]

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Table 1. Simulation parameters of multi-focus plenoptic camera
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Table 1. Simulation parameters of multi-focus plenoptic camera
Parameter ${f_{L}}_{}$ /mm b /mm B /mm ${s_{x}}_{}$ /μm ${s_{y}}_{}$ /μm ${r_{i}}_{}$ /pixel ${f_{m}}_{}$ /mm
Value 100 103.32 1.32 5 5 17 1.62, 1.92, 2.35

Table 2. Corner detection results on simulated datasets

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Table 2. Corner detection results on simulated datasets

Detection method	Recall /%	Precision /%	Mean /pixel	Std. /pixel	Time /s
Method in Ref. [16]	14.81	85.31	1.302	0.598	205920.73
Method in Ref. [17]	30.96	39.21	0.822	0.404	1232.90
Proposed method	59.47	99.26	0.276	0.218	958.44

Table 3. Calibration results on simulated datasets

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Table 3. Calibration results on simulated datasets

Calibration method	f_x	f_y	K₁	K₂	c_u	c_v	MRE /pixel
Method in Ref.[14]	19157.44	19158.12	-2.2119	7785.69	1476.69	982.36	-
Method in Ref.[16]	19095.37	19108.32	-2.1125	7789.89	1513.71	850.76	0.6609
Method in Ref.[17]	18979.45	18953.44	-2.4074	8083.23	1507.34	937.27	0.2325
Ours	19018.93	19028.72	-2.5763	8208.05	1485.49	976.05	0.1245
GT	19002.02	19002.02	-2.5265	8170.16	1500.00	1000.00	-

Table 4. Calibration results on R29 real dataset

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Table 4. Calibration results on R29 real dataset

Calibration method	f_x	f_y	K₁	K₂	c_u	c_v
Method in Ref.[14]	18513.01	18409.14	-2.8995	8728.17	3341.39	2183.02
Method in Ref.[16]	18609.03	18507.01	-2.6519	8592.60	3349.40	2229.08
Method in Ref.[17]	18513.01	18409.14	-2.8995	8728.17	3341.39	2183.02
Ours	18475.13	18374.66	-2.3976	7946.74	3377.06	2230.79

Table 5. Results of distance measurement

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Table 5. Results of distance measurement

Detection method	Calibration method	${D_{mean}}_{}$ /mm	${D_{std}}_{}$ /mm
Method in Ref. [17]	Method in Ref. [14]	3.45	13.98
	Method in Ref. [16]	9.75	14.15
	Method in Ref. [17]	2.35	14.85
	Ours	3.12	14.52
Proposed method	Method in Ref. [14]	3.85	3.68
	Method in Ref. [16]	8.48	3.84
	Method in Ref. [17]	4.35	3.58
	Ours	1.24	3.36

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Qingsong Liu, Xiaofang Xie, Xuanzhe Zhang, Yu Tian, Jun Li, Yan Wang, Xiaojun Xu. Checkerboard Corner Detection Algorithm for Calibration of Focused Plenoptic Camera[J]. Acta Optica Sinica, 2020, 40(14): 1415002

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