光学学报, 2020, 40 (14): 1415002, 网络出版: 2020-07-23 复制并引用该论文  本文已被引 9 次  被引通知

图 & 表

图 1. 相机成像模型。 (a)主透镜成像示意图; (b)微透镜成像示意图

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

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图 2. 角点检测结果。(a)初始角点检测结果; (b)去除微透镜边缘角点后的结果; (c) RANSAC算法拟合后的候选角点;(d)优化后的投影角点

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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图 3. 角点检测结果示例。(a)含有噪声的情况下; (b)图像含有较大镜头畸变的情况;(c)同一微透镜图像中存在多个角点的情况; (d)漏检的情况

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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图 4. 仿真标定图像示例

Fig. 4. Examples of images used in simulated calibration

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图 5. 测距实验装置及原理示意。(a)实验平台;(b)相对距离

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

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图 6. 角点重建结果。(a)本文结果;(b)参考文献[ 17]的结果

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

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表 1多焦距聚焦型光场相机的仿真参数

Table1. Simulation parameters of multi-focus plenoptic camera

Parameter fL /mm b /mm B /mm sx /μm sy /μm ri /pixel fm /mm Value 100 103.32 1.32 5 5 17 1.62, 1.92, 2.35

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表 2仿真数据集上的角点检测结果

Table2. 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

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表 3仿真数据集的标定结果

Table3. Calibration results on simulated datasets

Calibration method fx fy K1 K2 cu cv 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 -

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表 4R29真实数据集上的标定结果

Table4. Calibration results on R29 real dataset

Calibration method fx fy K1 K2 cu cv 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

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表 5距离测试结果

Table5. Results of distance measurement

Detection method Calibration method Dmean /mm Dstd /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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刘青松, 谢晓方, 张烜喆, 田瑜, 李俊, 王彦, 许晓军. 用于聚焦型光场相机标定的棋盘角点检测算法[J]. 光学学报, 2020, 40(14): 1415002. 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.