随机噪声平板下光学复眼内外参联合标定

李东升; 王国嫣; 刘锦新; 范红旗; 李飚

doi:10.11999/JEIT230652

随机噪声平板下光学复眼内外参联合标定

doi: 10.11999/JEIT230652

1.
国防科技大学ATR全国重点实验室长沙 410003
2.
桂林电子科技大学信息与通信学院桂林 541004

基金项目: 国家自然科学基金(62303478)

详细信息

作者简介:
李东升：男，博士生，研究方向为多目视觉SLAM，多源多目标信息融合等

王国嫣：女，讲师，研究方向为激光、多目视觉SLAM，多源信息融合，人机交互等。本文通信作者

刘锦新：男，博士生，研究方向为视觉SLAM，随机有限集等

范红旗：男，研究员，博士生导师，研究方向为信息融合，目标跟踪，雷达信号处理，智能导引系统，机器人技术等

李飚：男，研究员，博士生导师，研究方向为可见光/红外/THZ成像、成像目标探测跟踪与识别、人工智能图像处理以及实时系统设计技术等

通讯作者:
王国嫣　wangguoyan@nudt.edu.cn

中图分类号: TN
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- 被引次数: 0
出版历程
- 收稿日期: 2023-07-03
- 修回日期: 2024-05-01
- 网络出版日期: 2024-05-17

Joint Internal and External Parameters Calibration of Optical Compound Eye Based on Random Noise Calibration Pattern

1.
National University of Defense Technology, National Key Laboratory of Science and Technology on ATR, Changsha, 410003, China
2.
College of Information and Communication, Guilin University of Electronic Science and Technology, Guilin 541004, China

Funds: The National Nature Science Foundation of China (62303478)

摘要

摘要: 光学复眼在无人系统的精确定位制导、避障导航等任务中得到了越来越广泛的应用，其中光学复眼的高精度标定是保障上述任务质量的前提。通常经典的张氏棋盘格标定法要求光学复眼的每个子眼都必须观测到完整的棋盘格，然而，由于光学复眼结构的复杂性，使得在实际标定过程中难以满足这一要求。为解决张氏标定法的局限性，该文提出一种基于随机噪声平板的光学复眼内外参联合标定算法，该算法通过子眼拍摄随机噪声平板的局部信息，可简单快速的实现任意构型和子眼数量的光学复眼内外参联合标定。为了提高光学复眼标定的稳定性，设置多阈值匹配机制解决子眼视场特征点数量稀疏导致图像匹配失效的问题。同时，给出了光学复眼内外参联合标定的误差模型，用来衡量所提出算法的精确度。在与张氏棋盘格标定法进行实验对比中，验证所提算法的稳定性和鲁棒性，并在光学复眼实物系统中，验证了所提联合标定算法具有较高的精度。
- 光学复眼 /
- 随机噪声平板 /
- 内外参联合标定 /
- 平均重投影误差 /
- 广义相机模型
Abstract: In tasks such as precise guidance and obstacle avoidance navigation based on optical compound eyes, the calibration of optical compound eyes plays a crucial role in achieving high accuracy. The classical Zhang's calibration method requires each ommatidium of the optical compound eyes to observe a complete chessboard pattern. However, the complexity of the optical compound eye structure makes it difficult to satisfy this requirement in practical applications. In this paper, a joint internal and external parameters calibration algorithm of optical compound eyes based on a random noise calibration pattern is proposed. This algorithm utilizes the local information captured by the ommatidia when photographing the random noise calibration pattern, enabling simple and fast calibration for optical compound eyes with arbitrary configurations and numbers of ommatidia. To improve the robustness of the calibration, a multi-threshold matching mechanism is introduced to address the issue of sparse feature point quantity in ommatidial visual fields leading to matching failures. Moreover, an error model for the joint internal and external parameters calibration of optical compound eyes is presented to evaluate the accuracy of the proposed algorithm. Experimental comparisons with Zhang’s calibration method demonstrate the robustness of the proposed algorithm. Furthermore, the high accuracy of the proposed joint calibration algorithm is validated in a physical system of optical compound eyes.
- Optical compound eye /
- Random noise plate /
- Joint calibration of internal and external parameter /
- Average reprojection error /
- Generalized camera model

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图 1 标定板

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图 2 两两子眼标定模式

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图 3 计算外参重投影误差

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图 4 光学复眼模型俯视图

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图 5 光学复眼系统

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图 6 光学复眼成像

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图 7 标定板图像与子眼拍摄图像匹配结果

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图 8 棋盘格标定板

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图 9 子眼内参标定误差

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图 10 04号子眼标定示意图

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图 11 光学复眼与标定板姿态可视化图

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表 1 部分子眼对外部参数对比(°/pixel)

子眼对	本文方法	张氏棋盘格	本文方法(噪声)	张氏棋盘格(噪声)
01-05	54.97/0.23	53.42/0.27	54.44/0.22	57.72/0.58
01-09	175.20/0.23	178.92/0.26	177.63/0.22	177.63/0.44
02-09	48.71/0.23	47.38/0.22	49.13/0.22	46.48/0.35
06-07	54.12/0.23	54.33/0.31	55.26/0.22	54.97/0.46

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表 2 子眼内在参数

子眼	$ {f_x},{f_y} $	$ {o_u},{o_v} $	$ {k_1},{k_2},{p_1},{p_2} $	平均重投影误差(pixel)
01	177.89,236.81	159.70,125.26	0.0445, –0.0387, 0.0011, –0.0008	0.29
02	176.12,227.397	171.23,128.01	0.0324, –0.0396, 0.0066, –0.0091	0.33
03	172.933,254.3033	186.32,113.92	0.1419, –0.0760, –0.0187, 0.0142	0.34
04	191.69,259.85	178.81,120.80	0.0260, –0.03523, –0.0001, –0.0077	0.38
05	191.14,276.22	160.46, 137.70	0.1469, –0.0580, 0.0182, 0.0252	0.33
06	171.740,237.4745	182.34,114.06	–0.0024, –0.0082, 0.0098, –0.0013	0.31
07	202.45,261.1675	153.47,132.50	0.1506, –0.2704, –0.0066,0.0021	0.32
08	187.401,250.6387	184.73,115.53	0.0742, –0.1270, 0.0005, –0.0453	0.30
09	200.72,270.78	159.59,122.97	–0.0193, –0.0491, –0.0114, –0.0291	0.31

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表 3 子眼外部参数

外参	$ {\boldsymbol{T}} $(mm)	$ {{\boldsymbol{R}}_{om}} $(rad)
01-02	1210.27, –174.98, 118.74	–0.28863, –0.77946, 2.0756
01-03	216.34, 122.55, –56.82	–0.31501, –0.24960, 1.3377
01-04	–1132.90, –419.11, –408.43	0.55101, –0.34772, 0.81899
01-05	–111.479, 48.309, –519.68	–0.5102, –0.8016, 0.1326
01-06	–208.97, –399.07, 394.80	–0.00237, 0.52474, –0.5904
01-07	–167.19, 1142.11, –255.55	0.7406, –0.20962, –1.48558
01-08	198.78, 701.92, 1170.49	1.00398, 0.98246, –1.99923
01-09	–476.94, 101.36, 45.59	0.64625, 0.83267, –2.87042

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