Huai Jianzhu, Shao Yuxin, Jozkow Grzegorz, Wang Binliang, Chen Dezhong, He Yijia, Yilmaz Alper
The Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, 129 Luoyu Road, Wuhan 430079, China.
The Institute of Geodesy and Geoinformatics, Wroclaw University of Environmental and Life Sciences, 50-375 Wroclaw, Poland.
Sensors (Basel). 2024 Oct 13;24(20):6595. doi: 10.3390/s24206595.
Wide-angle cameras are widely used in photogrammetry and autonomous systems which rely on the accurate metric measurements derived from images. To find the geometric relationship between incoming rays and image pixels, geometric camera calibration (GCC) has been actively developed. Aiming to provide practical calibration guidelines, this work surveys the existing GCC tools and evaluates the representative ones for wide-angle cameras. The survey covers the camera models, calibration targets, and algorithms used in these tools, highlighting their properties and the trends in GCC development. The evaluation compares six target-based GCC tools, namely BabelCalib, Basalt, Camodocal, Kalibr, the MATLAB calibrator, and the OpenCV-based ROS calibrator, with simulated and real data for wide-angle cameras described by four parametric projection models. These tests reveal the strengths and weaknesses of these camera models, as well as the repeatability of these GCC tools. In view of the survey and evaluation, future research directions of wide-angle GCC are also discussed.
广角相机广泛应用于摄影测量和自动驾驶系统，这些系统依赖于从图像中获得的精确度量测量。为了找到入射光线与图像像素之间的几何关系，人们积极开展了几何相机校准（GCC）研究。旨在提供实用的校准指南，这项工作对现有的GCC工具进行了调查，并对广角相机的代表性工具进行了评估。该调查涵盖了这些工具中使用的相机模型、校准目标和算法，突出了它们的特性以及GCC发展的趋势。评估比较了六种基于目标的GCC工具，即BabelCalib、Basalt、Camodocal、Kalibr、MATLAB校准器和基于OpenCV的ROS校准器，使用由四种参数投影模型描述的广角相机的模拟数据和真实数据。这些测试揭示了这些相机模型的优缺点，以及这些GCC工具的可重复性。鉴于调查和评估，还讨论了广角GCC的未来研究方向。
