航空学报 > 2025, Vol. 46 Issue (4): 330860-330860   doi: 10.7527/S1000-6893.2024.30860

自适应Levenberg-Marquardt优化的低重叠度多相机精确标定方法

章涛, 高铂, 罗其俊()   

  1. 中国民航大学 天津市智能信号与图像处理重点实验室,天津 300300
  • 收稿日期:2024-06-24 修回日期:2024-08-05 接受日期:2024-10-10 出版日期:2024-11-08 发布日期:2024-11-07
  • 通讯作者: 罗其俊 E-mail:qjluo@cauc.edu.cn
  • 基金资助:
    国家重点研发计划(2022YFB3904303);中央高校基本科研业务费项目资助(3122018D002)

Adaptive Levenberg-Marquardt optimization for accurate calibration of multi-camera systems with low overlap fields of view

Tao ZHANG, Bo GAO, Qijun LUO()   

  1. Tianjin Key Laboratory for Advanced Signal Processing,Civil Aviation University of China,Tianjin 300300,China
  • Received:2024-06-24 Revised:2024-08-05 Accepted:2024-10-10 Online:2024-11-08 Published:2024-11-07
  • Contact: Qijun LUO E-mail:qjluo@cauc.edu.cn
  • Supported by:
    National Key Research and Development Program of China(2022YFB3904303);the Fundamental Research Funds for the Central Universities(3122018D002)

摘要:

机载视景智能辅助驾驶系统为了获取周边态势信息,需要进行大场景、低重叠、高精度的相机标定与危险目标位置测量。针对现有的低重叠度多目相机系统存在标定精度不足,且因畸变导致的视觉测量精度较低等问题,提出了一种自适应Levenberg-Marquardt优化的多相机精确标定方法。首先,建立了基于刚性组合标靶的双目相机标定模型,通过刚性固定的组合标靶和辅助相机,得到双目相机之间的转换关系。然后,提出自适应Levenberg-Marquardt优化算法,以标靶特征点的重投影误差为目标函数,采用自适应步长的迭代优化方法,对双目相机的转换矩阵进行优化,提高了标定精度。最后,完成多相机图像共圆心柱面投影,减少目标视差,提高拼接视景的测量精度。标定实验和测量实验结果表明,提出方法可解决低重叠度视场的相机精确标定与危险目标位置测量的问题,将重投影误差减小10%,测量误差减小13%。

关键词: 多相机系统, 相机标定, 自适应Levenberg-Marquardt优化算法, 全局校准, 柱面投影

Abstract:

To acquire situational awareness of the surroundings, pilot assistance systems require high-precision camera calibration and hazardous target position measurement in large-scale scenes with low overlap. To address the issues such as insufficient calibration accuracy in existing low-overlap multi-camera systems and reduced visual measurement accuracy due to distortion, this paper proposes a precise multi-camera calibration method based on adaptive Levenberg-Marquardt optimization. First, a binocular camera calibration model is established using a rigid composite target. By employing a rigidly fixed composite target and an auxiliary camera, the transformation relationship between the two cameras is derived. Then, an adaptive Levenberg-Marquardt optimization algorithm is introduced, which uses the reprojection error of the target’s feature points as the objective function. An iterative optimization method with adaptive step sizes is utilized to optimize the transformation matrix between the binocular cameras, thereby enhancing calibration accuracy. Finally, a co-centric cylindrical projection of multi-camera images is performed to reduce target parallax and improve the measurement accuracy of the stitched panoramic view. Calibration and measurement experiments demonstrate that the proposed method effectively addresses the challenges of precise camera calibration and hazardous target position measurement in low-overlapping fields of view, reducing the reprojection error by 10% and the measurement error by 13%.

Key words: multi-camera system, camera calibration, adaptive Levenberg-Marquardt optimization algorithm, global calibration, cylindrical projection

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